Programmer's Introduction
GNU Go Internals
utils.c
and printutils.c
Appendices
Indices
This is GNU Go 3.0, a Go program. Development versions of GNU Go may be
found at <http://www.gnu.org/software/gnugo/devel.html
>. Contact
us at gnugo@gnu.org if you are interested in helping.
The challenge of Computer Go is not to beat the computer, but to program the computer.
In Computer Chess, strong programs are capable of playing at the highest level, even challenging such a player as Garry Kasparov. No Go program even as strong as amateur shodan exists. The challenge is to write such a program.
To be sure, existing Go programs are strong enough to be interesting as opponents, and the hope exists that some day soon a truly strong program can be written.
GNU Go is getting stronger. For one thing, we've paid a lot of attention to life and death. GNU Go 3.0 can consistently give GNU Go 2.6 a four stone handicap. In a four stone game against GNU Go 2.6, GNU Go 3.0 very often kills a group.
Until now, Go programs have always been distributed as binaries only. The algorithms in these proprietary programs are secret. No-one but the programmer can examine them to admire or criticise. As a consequence, anyone who wished to work on a Go program usually had to start from scratch. This may be one reason that Go programs have not reached a higher level of play.
Unlike most Go programs, GNU Go is Free Software. Its algorithms and source code are open and documented. They are free for any one to inspect or enhance. We hope this freedom will give GNU Go's descendents a certain competetive advantage.
Here is GNU Go's Manual. There are doubtless inaccuracies. The ultimate documentation is in the commented source code itself.
The first three chapters of this manual are for the general user. Chapter 3 is the User's Guide. The rest of the book is for programmers, or persons curious about how GNU Go works. Chapter 4 is a general overview of the engine. Chapter 5 introduces various tools for looking into the GNU Go engine and finding out why it makes a certain move, and Chapters 6-7 form a general programmer's reference to the GNU Go API. The remaining chapters are more detailed explorations of different aspects of GNU Go's internals.
Copyright 1999, 2000, 2001 by the Free Software Foundation except for
the files gmp.c
and gmp.h
, which are copyrighted by
Bill Shubert (wms@igoweb.org).
All files are under the GNU General Public License (see GPL),
except gmp.c
, gmp.h
, gtp.c
, gtp.h
, the files
interface/html/*
and win/makefile.win
.
The two files gmp.c
and gmp.h
were placed in the public domain
by William Shubert, their author, and are free for unrestricted use.
The files gtp.c
and gtp.h
are copyright the Free Software
Foundation. In the interests of promoting the Go Text Protocol these
two files are licensed under a less restrictive license than the GPL
and are free for unrestricted use (see GTP License).
The files interface/html/*
are not part of GNU Go but are a separate
program and are included in the distribution for the convenience of anyone
looking for a CGI interface to GNU Go. They were placed in the public domain
by their author, Douglas Ridgway, and are free for unrestricted use. The file
win/makefile.win
is also in the public domain and is free for
unrestricted use.
GNU Go maintainers are Daniel Bump and Gunnar Farnebäck. GNU Go authors (in chronological order of contribution) are Man Li, Daniel Bump, David Denholm, Gunnar Farnebäck, Nils Lohner, Jerome Dumonteil, Tommy Thorn, Nicklas Ekstrand, Inge Wallin, Thomas Traber, Douglas Ridgway, Teun Burgers, Tanguy Urvoy, Thien-Thi Nguyen, Heikki Levanto, Mark Vytlacil, Adriaan van Kessel, Wolfgang Manner, Jens Yllman and Don Dailey.
We would like to thank Arthur Britto, Tim Hunt, Piotr Lakomy, Paul Leonard, Jean-Louis Martineau, Andreas Roever and Pierce Wetter for helpful correspondence. Thanks to everyone who stepped on a bug (and sent us a report)!
Thanks to Gary Boos, Peter Gucwa, Martijn van der Kooij, Michael Margolis, Trevor Morris, Mans Ullerstam, Don Wagner and Yin Zheng for help with Visual C++.
And thanks to Alan Crossman, Stephan Somogyi, Pierce Wetter and Mathias Wagner for help with Macintosh.
Special thanks to Ebba Berggren for creating our logo, based on a
design by Tanguy Urvoy and comments by Alan Crossman. The old
GNU Go logo was adapted from Jamal Hannah's typing GNU:
<http://www.gnu.org/graphics/atypinggnu.html
>.
Both logos can be found in doc/newlogo.*
and doc/oldlogo.*
.
We would like to thank Stuart Cracraft, Richard Stallman and Man Lung Li for their interest in making this program a part of GNU, William Shubert for writing CGoban and gmp.c, Rene Grothmann for Jago and Erik van Riper and his collaborators for NNGS.
You can help make GNU Go the best Go program.
This is a task-list for anyone who is interested in helping with GNU Go. If you want to work on such a project you should correspond with us until we reach a common vision of how the feature will work!
A note about copyright. The Free Software Foundation has the copyright to GNU Go. For this reason, before any code can be accepted as a part of the official release of GNU Go, the Free Software Foundation will want you to sign a copyright assignment.
Of course you could work on a forked version without signing such a disclaimer. You can also distribute such a forked version of the program so long as you also distribute the source code to your modifications under the GPL (see GPL). But if you want your changes to the program to be incorporated into the version we distribute we need you to assign the copyright.
Please contact the GNU Go maintainers, Daniel Bump (bump@math.stanford.edu) and Gunnar Farnebäck (gf@isy.liu.se), to get more information and the papers to sign.
Below is a list of things YOU could work on. We are already working on some of these tasks, but don't let that stop you. Please contact us or the person assigned to task for further discussion.
Bugs are an important cause of weakness in any Go program! If you can, send us bug FIXES as well as bug reports. If you see some bad behavior, figure out what causes it, and what to do about fixing it. And send us a patch! If you find an interesting bug and cannot tell us how to fix it, we would be happy to have you tell us about it anyway. Send us the sgf file (if possible) and attach other relevant information, such as the GNU Go version number. In cases of assertion failures and segmentation faults we probably want to know what operating system and compiler you were using, in order to determine if the problem is platform dependent.
See the texinfo manual in the doc directory for a description of how to do this. In particular it would be useful with test suites for common life and death problems. Currently second line groups, L groups and the tripod shape are reasonably well covered, but there is for example almost nothing on comb formations, carpenter's square, and so on. Other areas where test suites would be most welcome are fuseki, tesuji, and endgame.
This is a sort of art. It is not necessary to do any programming to do this since most of the patterns do not require helpers. We would like it if a few more Dan level players would learn this skill.
The semeai module is vastly in need of improvement. In fact, semeai can probably only be analyzed by reading to discover what backfilling is needed before we can make atari.
The connection analysis is today completely static and has a hard time identifying mutually dependent connections or moves that simultaneously threatens two or more connections. This could be improved by writing a connection reader, which like the owl code uses pattern matching to find a small amount of key moves to try.
GNU Go is reasonably accurate when it comes to tactical reading, but not always very fast. The main problem is that too many ineffective moves are tested, leading to strange variations that shouldn't need consideration. To improve this the move generation heuristics in the reading code needs to be refined. Some improvements should also be possible to obtain by tuning the move ordering.
In some positions GNU Go may report a group as alive or connected with a living group. But after the opponent has placed one stone GNU Go may change the status to dead, without going through a critical status. It would be nice if these positions could be automatically identified and logged for later analysis.
You can get the most recent version of GNU Go ftp.gnu.org or a mirror
(see <http://www.gnu.org/order/ftp.html
> for a list). You can read
about newer versions and get other information at
<http://www.gnu.org/software/gnugo/
>.
Untar the sources, change to the directory gnugo-3.0.0. Now do:
./configure [OPTIONS] make
The most important configure options, cache size, default level and dfa will be explained in detail in the next section (see Configure Options). Probably you do not need to set these unless you are dissatisfied with GNU Go's performance for any reason.
As an example,
./configure --enable-cache-size=32 --enable-level=8
creates a 48 Mb cache in RAM and sets the level to 8. Both these defaults can be overridden at run time.
If you do not specify any options, the default level is 10 (highest supported), and the default cache size is 16, and the DFA is not enabled.
If you have a slow machine or find GNU Go too slow you may want to decrease the default level. At level 8 the engine is playing about 1.6 times faster than at level 10.
Increasing the cache size will improve performance up to a point -- once the cache is so large that it cannot be kept in RAM, GNU Go will start swapping (characterized by frequent hard drive accesses) and performance will degrade.
You have now made a binary called interface/gnugo
. Now
(running as root) type
make install
to install gnugo in /usr/local/bin
.
There are different methods of using GNU Go. You may run it from the command line by just typing:
gnugo
but it is nicer to run it using CGoban 1 (under X-Windows) or Jago (on any platform with a Java runtime environment).
You can get the most recent version of CGoban 1 from Bill Shubert's web site:
<http://www.igoweb.org/~wms/comp/cgoban/index.html
> The CGoban version
number MUST be 1.9.1 at least or it won't work. CGoban 2 will not work.
See CGoban, for instructions on how to run GNU Go from Cgoban, or See Jago, for Jago.
There are three options which you should consider configuring, particularly if you are dissatisfied with GNU Go's performance.
By default, GNU Go makes a cache of 16 Megabytes in RAM for its internal use. The cache is used to store intermediate results during its analysis of the position.
Increasing the cache size will often give a modest speed improvement. If your system has lots of RAM, consider increasing the cache size. But if the cache is too large, swapping will occur, causing hard drive accesses and degrading performance. If your hard drive seems to be running excessively your cache may be too large. On GNU/Linux systems, you may detect swapping using the program 'top'. Use the 'f' command to toggle SWAP display.
You may override the size of the default cache at compile time by running one of:
./configure --enable-cache-size=n
to set the cache size to n
megabytes. For example
./configure --enable-cache-size=48
creates a cache of size 48 megabytes. If you omit this, your default
cache size will be 16 MB. You must recompile and reinstall
GNU Go after reconfiguring it by running make
and
make install
.
You may override the compile-time defaults by running gnugo with the
option --cache-size n
, where n
is the size in
megabytes of the cache you want, and --level
where n is the
level desired. We will discuss setting these parameters next in detail.
GNU Go can play at different levels. Up to level 10 is supported. At level 10 GNU Go is much more accurate but takes an average of about 1.6 times longer to play than at level 8.
The level can be set at run time using the --level
option.
If you don't set this, the default level will be used. You
can set the default level with the configure option
--enable-level=n
. For example
./configure --enable-level=9
sets the default level to 9. If you omit this parameter, the compiler sets the default level to 10. We recommend using level 10 unless you find it too slow. If you decide you want to change the default you may rerun configure and recompile the program.
If you ./configure --enable-dfa
you get the experimental DFA
(Discrete Finite-State Automata) pattern matcher. This will result in a
larger but somewhat faster engine. The option is considered experimental
because it is new and harder to debug but sufficiently tested that it is
probably safe.
GNU Go is being developed on Unix variants. GNU Go is easy to build and install on those platforms. GNU Go 3.0 has support for building on MS-DOS, Windows 3.x, Windows NT/2000 and Windows 95/98.
There are two approaches to building GNU Go on Microsoft platforms.
One benefit of this approach is that it is easier to participate in Gnu Go's development. These unix environments come for instance with the `diff' and `patch' programs necessary to generate and apply patches.
Another benefit of the unix environments is that development versions (which may be stronger than the latest stable version) can be built too. The supporting files for VC are not always actively worked on and consequently are often out of sync for development versions, so that VC will not build cleanly.
The rest of this section gives more details on the various ways to compile GNU go for Microsoft platforms.
On these platforms DJGPP can be used. GNU Go installation has been tested in a DOS-Box with long filenames on Windows 95/98. GNU Go compiles out-of-the box with the DJGPP port of GCC using the standard Unix build and install procedure.
Some URLs for DJGPP:
DJGPP home page: <http://www.delorie.com/djgpp/
>
DJGPP ftp archive on simtel:
<ftp://ftp.simtel.net/pub/simtelnet/gnu/djgpp/v2/
>
<ftp://ftp.simtel.net/pub/simtelnet/gnu/djgpp/v2gnu/
>
Once you have a working DJGPP environment and you have downloaded the gnugo source available as gnugo-3.0.0.tar.gz you can build the executable as follows:
tar zxvf gnugo-3.0.0.tar.gz cd gnugo-3.0.0 ./configure make
Optionally you can download glib for DJGPP to get a working version of snprintf.
On these platforms the Cygwin environment can be installed. Recent
versions of Cygwin install very easily with the setup program available
from the cygwin homepage. <<http://sourceware.cygnus.com/cygwin/
>.
GNU Go compiles out-of-the box using the standard Unix build procedure
on the Cygwin environment. After installation of cygwin and fetching
gnugo-3.0.0.tar.gz
you can type:
tar zxvf gnugo-3.0.0.tar.gz cd gnugo-3.0.0 ./configure make
The generated executable is not a stand-alone executable: it needs cygwin1.dll that comes with the Cygwin environment. cygwin1.dll contains the emulation layer for Unix.
Cygwin Home page: <http://sourceware.cygnus.com/cygwin/
>
Optionally you can use glib to get a working version of snprintf. Glib builds out of the box on cygwin.
The Cygwin environment also comes with MinGW32. This generates an executable that relies only on Microsoft DLLs. This executable is thus completely comparable to a Visual C executable and easier to distribute than the Cygwin executable. To build on cygwin an executable suitable for the win32 platform type the following at your cygwin prompt:
tar zxvf gnugo-3.0.0.tar.gz cd gnugo-3.0.0 env CC='gcc -mno-cygwin' ./configure make
We assume that you do not want to change any configure options.
If you do, you should edit the file config.vc
. Note that
when configure
is run, this file is overwritten with
the contents of config.vcin
, so you may also want to edit
config.vcin
, though the instructions below do not have
you running configure
.
Notes:
msdev gnugo.dsw /make "gnugo - Win32 Release"
FILE MKPAT OPTIONS INPUT FILES conn.c mkpat -c conn conn.db patterns.c mkpat -b pat patterns.db, patterns2.db apatterns.c mkpat -X attpat attack.db dpatterns.c mkpat defpat defense.db influence.c mkpat -c influencepat influence.db endgame.c mkpat -b endpat endgame.db owl_attackpat.c mkpat -b owl_attackpat owl_attackpats.db owl_vital_apat.c mkpat -b owl_vital_apat owl_vital_apats.db owl_defendpat.c mkpat -b owl_defendpat owl_defendpats.db fuseki9.c mkpat -b -f fuseki9 fuseki9.db fuseki19.c mkpat -b -f fuseki19 fuseki19.db josekidb.c mkpat -b joseki hoshi.db, komoku.db, sansan.db, takamoku.db mokuhazushi.db
GNU Go does not come with its own graphical user interface. The Java client jago can be used.
To run Jago you need a Java Runtime Environment (JRE). This can
be obtained from <http://www.javasoft.com/
>. This is the runtime
part of the Java Development Kit (JDK) and consists of the Java
virtual machine, Java platform core classes, and supporting files.
The Java virtual machine that comes with I.E. 5.0 works also.
Jago: <http://mathsrv.ku-eichstaett.de/MGF/homes/grothmann/jago/Go.html
>
gnugo --quiet --mode gmp
gnugo --help
from a cygwin or DOS window for a list of
options
--level <level>
to make the game faster
Jago works well with both the Cygwin and MinGW32 executables. The DJGPP executable also works, but has some problems in the interaction with jago after the game has been finished and scored.
If you have Mac OS X you can build GNU Go using Apple's compiler, which is derived from GCC. We recommend adding the flag -no-cpp-precom to CFLAGS.
You can obtain a printed copy of the manual by running
make gnugo.ps
in the doc/
directory, then printing the
resulting postscript file. The manual contains a great deal of information
about the algorithms of GNU Go.
On platforms supporting info documentation, you can usually
install the manual by executing `make install' (running as
root) from the doc/
directory. The info documentation can
be read conveniently from within Emacs by executing the
command Control-h i
.
Documentation in doc/
consists of a man page gnugo.6
, the
info files gnugo.info
, gnugo.info-1
, ... and the
Texinfo files from which the info files are built. The Texinfo
documentation contains this User's Guide and extensive information
about the algorithms of GNU Go, for developers.
If you want a typeset copy of the Texinfo documentation, you can
make gnugo.dvi
or make gnugo.ps
in the doc/
directory.
You can make an HTML version with the command makeinfo
--html gnugo.texi
. Better HTML documentation may be obtained
using texi2html -split_chapter gnugo.texi
. You can
obtain the texi2html
utility (version 1.61 or later) from
<http://www.mathematik.uni-kl.de/~obachman/Texi2html/
>. (See also
<http://texinfo.org/texi2html/
>.)
User documentation can be obtained by running gnugo --help
or man gnugo
from any terminal, or from the Texinfo
documentation.
Documentation for developers is in the Texinfo documentation, and in comments throughout the source. Contact us at gnugo@gnu.org if you are interested in helping to develop this program.
This is an extremely nice way to run GNU Go. CGoban provides a beautiful graphic user interface under X-Windows.
Start CGoban. When the CGoban Control panel comes up, select "Go Modem". You will get the Go Modem Protocol Setup. Choose one (or both) of the players to be "Program," and fill out the box with the path to gnugo. After clicking OK, you get the Game Setup window. Choose "Rules Set" to be Japanese (otherwise handicaps won't work). Set the board size and handicap if you want.
If you want to play with a komi, you should bear in mind that
the GMP does not have any provision for communicating the komi.
Because of this misfeature, unless you set the komi at the command
line GNU Go will have to guess it. It assumes the komi is 5.5 for
even games, 0.5 for handicap games. If this is not what you want,
you can specify the komi at the command line with the
--komi
option, in the Go Modem Protocol Setup window.
You have to set the komi again in the Game Setup window, which
comes up next.
Click OK and you are ready to go.
In the Go Modem Protocol Setup window, when you specify the path to
GNU Go, you can give it command line options, such as --quiet
to
suppress most messages. Since the Go Modem Protocol preempts standard
I/O other messages are sent to stderr, even if they are not error
messages. These will appear in the terminal from which you started
CGoban.
Even if you do not have CGoban installed you can play with GNU Go
using its default Ascii interface. Simply type gnugo
at the command line, and GNU Go will draw a board. Typing
help
will give a list of options. At the end of the
game, pass twice, and GNU Go will prompt you through the
counting. You and GNU Go must agree on the dead groups--you
can toggle the status of groups to be removed, and when you
are done, GNU Go will report the score.
You can save the game at any point using the save filename
command. You can reload the game from the resulting SGF file with
the command gnugo -l filename --mode ascii
. Reloading
games is not supported when playing with CGoban. However you can
use CGoban to save a file, then reload it in ascii mode.
You can run GNU Go from Emacs. This has the advantage that you place the stones using the cursor arrow keys. This may require Emacs 20.4 or later--it has been tested with Emacs 20.4 but does not work with Emacs 19 or Emacs 20.2.
Load interface/gnugo.el
, either by M-x load-file
,
or by copying the file into your site-lisp
directory and
adding a line
(autoload 'gnugo "gnugo" "GNU Go" t)
in your .emacs
file.
Now you may start GNU Go by M-x gnugo
. You will be prompted for
command line options see Invoking GNU Go. Using these, you may set the
handicap, board size, color and komi.
You can enter commands from the GNU Go ASCII interface after
typing :
. For example, to take a move back, type
:back
, or to list all commands, type :help
.
Here are the default keybindings:
Return
or Space
Select point as the next move. An error is signalled for invalid locations. Illegal locations, on the other hand, show up in the GNUGO Console buffer.
q
or Q
Quit. Both Board and Console buffers are deleted.
R
Resign.
C-l
Refresh. Includes restoring default window configuration.
M-_
Bury both Board and Console buffers (when the boss is near).
p
Pass; i.e., select no location for your move.
:
Extended command. After typing the :
you can type a
command for GNU Go. The possible commands are as in See Ascii.
Jago, like CGoban is a client capable of providing GNU Go with a graphical user interface. Unlike CGoban, it does not require X-Windows, so it is an attractive alternative under Windows. You will need a Java runtime environment. Obtain Jago at
<http://mathsrv.ku-eichstaett.de/MGF/homes/grothmann/jago/Go.html
>
and follow the links there for the Java runtime environment.
The Go Modem Protocol (GMP) was developed by Bruce Wilcox with input from
David Fotland, Anders Kierulf and others, according to the history in
<http://www.britgo.org/tech/gmp.html
>.
Any Go program should support this protocol since it is a standard. Since CGoban supports this protocol, the user interface for any Go program can be done entirely through CGoban. The programmer can concentrate on the real issues without worrying about drawing stones, resizing the board and other distracting issues.
GNU Go 3.0 introduces a new protocol, the Go Text Protocol (see GTP) which we hope can serve the functions currently used by the GMP.
Computer Tournaments currently use the Go Modem Protocol.
The current method followed in such tournaments is to connect
the serial ports of the two computers by a "null modem" cable.
If you are running GNU/Linux it is convenient to use CGoban.
If your program is black, set it up in the Go Modem Protocol
Setup window as usual. For White, select "Device" and set
the device to /dev/cua0
if your serial port is COM1
and /dev/cua1
if the port is COM2.
The Smart Go Format (SGF), is the standard format for storing Go games.
GNU Go supports both reading and writing SGF files. The SGF specification
(FF[4]) is at:
<http://www.red-bean.com/sgf/
>
--help
, -h
Print a help message describing the options. This will also tell you the defaults of various parameters, most importantly the level and cache size. The default values of these parameters can be set before compiling byconfigure
. If you forget the defaults you can find out using--help
.
--boardsize size
Set the board size
--komi num
Set the komi
--level level
GNU Go can play with different strengths and speeds. Level 10 is the default. Decreasing the level will make GNU Go faster but less accurate in its reading.
--quiet
, --silent
Don't print copyright and other messages. Messages specifically
requested by other command line options, such as --trace
,
are not supressed.
-l
, --infile filename
Load the named SGF file
-L
, --until move
Stop loading just before the indicated move is played. move can be either the move number or location.
-o
, --outfile filename
Write sgf output to file
--mode mode
Force the playing mode ('ascii', 'test,' 'gmp' or 'gtp'). The default is ASCII, but if no terminal is detected GMP (Go Modem Protocol) will be assumed. In practice this is usually what you want, so you may never need this option.
-M
, --cache-size megs
Memory in megabytes used for hashing. The default size is 16 unless you configure gnugo with the commandconfigure --enable-cache-size=size
before compiling to make size the default (see Installation). GNU Go stores results of its reading calculations in a Hash table (see Hashing). If the Hash table is filled, it is emptied and the reading continues, but some reading may have to be repeated that was done earlier, so a larger cache size will make GNU Go run faster, provided the cache is not so large that swapping occurs. Swapping may be detected on GNU/Linux machines using the programtop
. However if you have ample memory or if performance seems to be a problem may want to increase the size of the Hash cache using this option.
--chinese-rules
Use Chinese rules. This means that the Chinese or Area Counting is followed. It may affect the score of the game by one point in even games, more if there is a handicap (since in Chinese Counting the handicap stones count for Black).
--japanese-rules
Use Japanese Rules. This is the default unless you specify
--enable-chinese-rules
as a configure option.
--copyright
: Display the copyright notice
--version
or -v
: Print the version number
--printsgf filename
: Create an SGF file
containing a diagram of the board. Useful with -L
to
create diagrams from games.
The single parameter --level
is a convenient way of
choosing whether to play stronger or faster. This single
parameter controls a host of other parameters which may
optionally be set individually at the command line. The
default values of these parameters may be found by running
gnugo --help
. Unless you are working on the program
you probably don't need these options. Instead, just adjust the
single variable --level
.
These options are of use to developers tuning the program for performance and accuracy.
-D
, --depth depth
Deep reading cutoff. When reading beyond this depth (default 14) GNU Go assumes that any string which can obtain 3 liberties is alive. Thus GNU Go can read ladders to an arbitrary depth, but will miss other types of capturing moves.
--branch-depth
This sets thebranch_depth
, typically a little below thedepth
. Betweenbranch_depth
anddepth
, attacks on strings with 3 liberties are considered but branching is inhibited, so fewer variations are considered.
-B
, --backfill-depth depth
Deep reading cutoff. Beyond this depth (default 9) GNU Go will no longer try backfilling moves in its reading.
--backfill2-depth depth
Another depth controlling how deeply GNU Go looks for backfilling moves. The moves tried belowbackfill2_depth
are generally more obscure and time intensive than those controlled bybackfill_depth
, so this parameter has a lower default.
-F
, --fourlib-depth depth
Deep reading cutoff. When reading beyond this depth (default 5) GNU Go assumes that any string which can obtain 4 liberties is alive.
-K
, --ko-depth depth
Deep reading cutoff. Beyond this depth (default 8) GNU Go no longer tries very hard to analyze kos.
--branch-depth depth
Deep reading cutoff. Below this depth (default 8), GNU Go still tries to attack strings with only 3 liberties, but only tries one move at each node.
--aa_depth depth
The reading functionatari_atari
looks for combinations beginning with a series of ataris, and culminating with some string having an unexpected change in status (e.g. alive to dead or critical). This command line optio sets the parameteraa_depth
which determines how deeply this function looks for combinations.
--superstring-depth
A superstring (see Superstrings) is an amalgamation of
tightly strings. Sometimes the best way to attack or defend a
string is by attacking or defending an element of the superstring.
Such tactics are tried below superstring_depth
and this
command line option allows this parameter to be set.
The preceeding options are documented with the reading code (see Reading Basics).
owl-branch
Below this depth Owl only considers one move. Default 8.
owl-reading
Below this depth Owl assumes the dragon has escaped.
Default 20.
owl-node-limit
If the number of variations exceeds this limit,
Owl assumes the dragon can make life. Default 10000. We caution the user that
increasing owl_node_limit
does not necessarily increase the strength of
the program.
--level amount
The higher the level, the deeper GNU Go reads. Level 10 is the default. If GNU Go plays too slowly on your machine, you may want to decrease it.
--color color
Choose your color ('black' or 'white')
--handicap number
Choose the number of handicap stones (0-9)
--replay color
Replay all moves in a game for either or both colors. If used with the-o
option the game record is annotated with move values. This option requires-l filename
. The color can be:When the move found by genmove differs from the move in the sgf file the values of both moves are reported thus:
- white: replay white moves only
- black: replay black moves only
- both: replay all moves
Move 13 (white): GNU Go plays C6 (20.60) - Game move F4 (20.60)This option is useful if one wants to confirm that a change such as an speedup or other optimization has not affected the behavior of the engine. Note that when the several moves have the same top value (or nearly equal) the move generated is not deterministic (though it can be made deterministic by starting with the same random seed). Thus a few deviations from the move in the sgf file are to be expected. Only if the two reported values differ should we conclude that the engine plays differently from the engine which generated the sgf file. See Regression.
-a
, --allpats
Test all patterns, even those smaller in value than the largest move
found so far. This should never affect GNU Go's final move, and it
will make it run slower. However this can be very useful when "tuning"
GNU Go. It causes both the traces and the output file (-o
) to
be more informative.
-T
, --printboard
: colored display of dragons.
Use rxvt, xterm or Linux Console. (see Colored Display)
-E
: colored display of eye spaces
Use rxvt, xterm or Linux Console. (see Colored Display)
-d
, --debug level
Produce debugging output. The debug level is given in hexadecimal, using the bits defined in the following table fromengine/gnugo.h
.
- DEBUG_INFLUENCE 0x0001
- DEBUG_EYES 0x0002
- DEBUG_OWL 0x0004
- DEBUG_ESCAPE 0x0008
- DEBUG_MATCHER 0x0010
- DEBUG_DRAGONS 0x0020
- DEBUG_SEMEAI 0x0040
- DEBUG_LOADSGF 0x0080
- DEBUG_HELPER 0x0100
- DEBUG_READING 0x0200
- DEBUG_WORMS 0x0400
- DEBUG_MOVE_REASONS 0x0800
-H
, --hash level
hash (see engine/gnugo.h
for bits).
-w
, --worms
Print more information about worm data.
-m
, --moyo level
moyo debugging, show moyo board. The level is fully documented elsewhere (see Colored Display).
-b
, --benchmark number
benchmarking mode - can be used with -l
.
-s
, --stack
stack trace (for debugging purposes).
-S
, --statistics
Print statistics (for debugging purposes).
-t
, --trace
Print debugging information. Use twice for more detail.
-r
, --seed seed
Set random number seed. This can be used to guarantee that GNU Go will make
the same decisions on multiple runs through the same game. If seed
is
zero, GNU Go will play a different game each time.
--decide-string location
Invoke the tactical reading code (see Tactical Reading to decide
whether the string at location can be captured, and if so, whether it
can be defended. If used with -o
, this will produce a variation tree
in SGF.
--decide-dragon location
Invoke the owl code (see The Owl Code) to decide whether the dragon at
location can be captured, and whether it can be defended. If used with
-o
, this will produce a variation tree in SGF.
--score method
Requires-l
. method can be "end", "last", "aftermath" or a move. "end" and "aftermath" are appropriate when the game is complete, or nearly so, and both try to supply an accurate final score. The other options may be used to get an estimate during the middle of the game. Any of these options may be combined with--chinese-rule
if you want to use Chinese (Area) counting.
- last
load the sgf file up to the last move, then estimate territory using the Bouzy 5/21 algorithm (see Moyo).- end
finish the game by selfplaying from the end of the file until two passes, then estimate territory using the Bouzy 5/21 algorithm (see Moyo).- aftermath
finish the game by selfplaying from the end of the file until two passes, then estimate territory using the most accurate scoring algorithm available. Slower than--score last
, and while these algorithms usually agree, if they differ,--score aftermath
is most likely to be correct.- move, e.g.
--score J17
load file until move is reached and estimate territorial balance using the Bouzy 5/21 algorithm. The--score end
and--score aftermath
options are only useful at or near the end of the game, so if you want an estimate of the score in the middle, use this method.
--printsgf output file
load SGF file, output final position (requires-l
) as another SGF file. Illegal moves are indicated with the privateIL
property. This property is not used in the FF4 SGF specification, so we are free to preempt it. This feature is used in the CGI interface ininterface/html/gg.cgi
.
This chapter is an overview of the GNU Go internals. Further documentation of how any one module or routine works may be found in later chapters or comments in the source files.
examine_position()
does.
genmove()
.
A worm is a maximal set of vertices on the board which are connected
along the horizontal and vertical lines, and are of the same color,
which can be BLACK
, WHITE
or EMPTY
. The term
EMPTY
applied to a worm means that the worm consists of empty
(unoccupied) vertices. It does not mean that that the worm is the
empty set. A string is a nonempty worm. An empty worm is called a
cavity. If a subset of vertices is contained in a worm, there is a unique
worm containing it; this is its worm closure. (see Worms.)
A dragon is a union of strings of the same color which will be treated as a unit. If two strings are in the same dragon, it is the computer's working hypothesis that they will live or die together and are effectively connected. (see Dragons.)
A superstring is a less commonly used unit which is the union
of several strings but generally smaller than a dragon. The superstring
code is in engine/utils.c
. The definition of a superstring is
slightly different if the code is called from owl.c
or from
reading.c
.
The engine of GNU Go takes a positions and a color to move and
generates the (supposedly) optimal move. This is done by the function
genmove()
in engine/genmove.c
.
The move generation is done in three passes:
The information gathering is done by a function examine_position()
,
which will be discussed in greater detail in the next section.
Such information could be life and death of the groups, information
about moyos, connection of groups and so on. Information gathering is
performed by examine_position
, which in turn calls:
make_worms()
Collect information about all connected sets of stones
(strings) and cavities. This information is stored in
the worm[][]
array. (see Worms)
compute_initial_influence()
Decides which areas of the board are influenced by which
player. This function is run a second time later at
the end of make_dragons()
, since GNU Go's opinion
about the safety of groups may change, and it is
important to have the influence function as accurate as
possible. see Influence
make_dragons()
Collect information about connected strings, which are called dragons. Important information here is number of eyes, life status, and connectedness between string. (see Dragons.)
A more detailed
Once we have found out all about the position it is time to generate the best move. Moves are proposed by a number of different modules called move generators. The move generators themselves do not set the values of the moves, but enumerate justifications for them, called move reasons. The valuation of the moves comes last, after all moves and their reasons have been generated.
The move generators in version 3.0 are:
fuseki()
Generate a move in the early fuseki.
semeai()
Find out if two dead groups of opposite colors are next to each other and, if so, try to kill the other group. This module will eventually be rewritten along the lines of the owl code.
shapes()
Find patterns frompatterns/patterns.db
in the current position. Each pattern is matched in each of the 8 possible orientations obtainable by rotation and reflection. If the pattern matches, a so called "constraint" may be tested which makes use of reading to determine if the pattern should be used in the current situation. Such constraints can make demands on number of liberties of strings, life and death status, and reading out ladders, etc. The patterns may call helper functions, which may be hand coded (inpatterns/helpers.c
) or autogenerated.The patterns can be of a number of different classes with different goals. There are e.g. patterns which try to attack or defend groups, patterns which try to connect or cut groups, and patterns which simply try to make good shape. In addition to the large pattern database called by
shapes()
, pattern matching is used by other modules for different tasks throughout the program. See Patterns, for a complete documentation of patterns.
atari_atari()
See if there are any combination threats and either propose them or defend against them.
owl_reasons()
The Owl Code (see The Owl Code) which has been run duringexamine_position
), beforeowl_reasons()
executes, has decided whether different groups can be attacked. The modulereview_owl_reasons
reviews the statuses of every dragon and assigns move reasons for attack and defense. Unlike the other move generation modules, this one is called fromexamine_position()
.
endgame_shapes()
If no move is found with a value greater than 6.0, this module matches a
set of extra patterns which are designed for the endgame. The endgame
patterns can be found in patterns/endgame.db
.
revise_semeai()
If no move is found, this module changes the status of opponent groups involved in a semeai fromDEAD
toUNKNOWN
. After this, genmove runsshapes
andendgame_shapes
again to see if a new move turns up.
fill_liberty()
Fill a common liberty. This is only used at the end of the game. If necessary a backfilling or backcapturing move is generated.
After the move generation modules have run, the best ten moves
are selected by the function review_move_reasons
. This
function also does some analysis to try to turn up other moves
which may have been missed. The modules revise_semeai()
and
fill_liberty
are only run if no good move has been
discovered by the other modules.
In this section we summarize the sequence of events when
examine_position()
is run from genmove()
. This
is for reference only. Don't try to memorize it.
purge persistent reading cache (see Persistent Cache)make_worms()
(see Worms):build_worms()
finds and identifies the worms compute effective size of each wormunconditional_life()
find_worm_attacks_and_defenses()
: for each attackable worm: setworm.attack
add_attack_move()
find_attack_patterns()
to find a few more attacks for each defensible worm setworm.defend
add_defense_move
if point of attack is not adjacent to worm see if it defendsfind_defense_patterns()
to find a few more defenses for each attackable worm try each liberty if it attacksadd_attack_move
if it defendsadd_defense_move
find kos. for each worm find higher order liberties find cutting points (worm.cutstone) for each worm compute the genus (see Worms)small_semeai()
try to improve values of worm.attack and worm.defend try to repair situations where adjacent worms can be both attacked and defended find worm lunches find worm threatscompute_initial_influence()
(see Influence)compute_influence()
find_influence_patterns()
at each intersectionaccumulate_influence()
segment_influence()
make_dragons()
(see Dragons) initialize dragon data find the inessential wormsmake_domains()
initialize eye datacompute_primary_domains()
fill out arrays black_eye and white_eye describing eyeshapes find_cuts() for every eyespaceoriginate_eye()
count_neighbors()find_connections()
amalgamate dragons sharing an eyespaceinitialize_supplementary_dragon_data()
find adjacent worms which can be captured (dragon lunches) find topological half eyes and false eyesmodify_eye_spaces()
for each eye spacecompute_eyes()
store the results in black_eye, white_eye arrays compute the genus of each dragon for each dragoncompute_escape()
resegment_initial_influence()
for each dragoninfluence_get_moyo_size()
for each dragoncompute_dragon_status()
find_neighbor_dragons()
purge_persistent_owl_cache()
for each dragon which seems surrounded tryowl_attack()
andowl_defend()
if appropriate find owl threats for each dragon set dragon.matcher_status for each dragon set dragon2.safetysemeai()
revise opinion of which worms are inessential count non-dead dragons of each colorowl_reasons()
(see The Owl Code)compute_initial_influence()
again (see Influence)
In this section we summarize the sequence of events during the
move generation and selection phases of genmove()
, which
take place after the information gathering phase has been completed.
fuseki()
shapes()
review_move_reasons()
find_more_attack_and_defense_moves()
remove_opponent_attack_and_defense_moves()
do_remove_false_attack_and_defense_moves()
examine_move_safety()
induce_secondary_move_reasons()
value_moves()
find the ten best moves if the value of the best move is < 6.0endgame_shapes()
if no move found yetrevise_semeai()
shapes()
endgame_shapes()
if still no move foundfill_liberty()
if still no move found pass
The GNU Go engine is contained in two directories, engine/
and
patterns/
. Code related to the user interface, reading and
writing of smart go format files and testing are found in
the directories interface/
, sgf/
, and
regression/
. Code borrowed from other GNU programs is
contained in utils/
. Documentation is in doc/
.
In this document we will describe some of the individual files comprising
the engine code in engine/
and patterns/
. In interface/
we mention two files:
gmp.c
This is the Go Modem Protocol interface (courtesy of William Shubert and others). This takes care of all the details of exchanging setup and moves with Cgoban, or any other driving program recognizing the Go Modem Protocol.
main.c
This containsmain()
. Thegnugo
target is thus built in theinterface/
directory.
engine/
In engine/
there are the following files:
aftermath.c
Contains algorithms which may be called at the end of the game to generate moves that will generate moves to settle the position, if necessary playing out a position to determine exactly the status of every group on the board, which GNU Go can get wrong, particularly if there is a seki. This module is the basis for the most accurate scoring algorithm available in GNU Go.
board.c
This file contains code for the maintenance of the board. For example it contains the important functiontrymove()
which tries a move on the board, andpopgo()
which removes it by popping the move stack. At the same time vital information such as the number of liberties for each string and their location is updated incrementally.
clock.c
Clock code, including code allowing GNU Go to automatically adjust its level in order to avoid losing on time in tournaments.
dragon.c
This containsmake_dragons()
. This function is executed before the move-generating modulesshapes()
semeai()
and the other move generators but aftermake_worms
. It tries to connect worms into dragons and collect important information about them, such as how many liberties each has, whether (in GNU Go's opinion) the dragon can be captured, if it lives, etc.
fuseki.c
Generates fuseki (opening) moves from a database.
filllib.c
Code to force filling of dame (backfilling if necessary) at the end of the game.
genmove.c
This file containsgenmove()
and its supporting routines, particularlyexamine_position()
.
globals.c
This contains the principal global variables used by GNU Go.
gnugo.h
This file contains declarations forming the public interface to the engine.
hash.c
and cache.c
Hashing code implementing Zobrist hashing. (see Hashing) The code inhash.c
provides a way to hash board positions into compact descriptions which can be efficiently compared. The code incache.c
implements a kind of database for storing reading results, so they can be quickly retrieved. The caching code uses the board hashes as keys to the database. They are split since these functionalities are sufficiently demarked that either file could be reimplemented without affecting the other one. Note also thatmatchpat()
uses the hashing code without also using the caching code.
hash.h
and cache.h
Header files forhash.c
andcache.c
.
influence.c
and influence.h
.
This code determines which regions of the board are under the influence of either player. (see Influence)
liberty.h
Header file for the engine. The name "liberty" connotes freedom (see Copying).
life.c
The code in this file contains an alternative approach to life and death based on reading instead of the static approach inoptics.c
. This code is experimental. It is reasonably accurate but too slow. It is activated when gnugo is invoked with the--life
option.
matchpat.c
This file contains the pattern matchermatchpat()
, which looks for patterns at a particular board location. The actual patterns are in thepatterns/
directory. The functionmatchpat()
is called by every module which does pattern matching, notablyshapes
.
move_reasons.c
This file contains the code which assigns values to every move after all the move reasons are gen
optics.c
This file contains the code to recognize eye shapes, documented in See Eyes.
owl.c
This file does life and death reading. The paradigm is that moves are played by both players trying to expand and shrink the eyespace until a static configuration is reached where it can be analyzed by the code inoptics.c
orlife.c
.
printutils.c
Print utilities
reading.c
This file contains code to determine whether any given string can be attacked or defended. See Tactical Reading, for details.
score.c
Implements the Bouzy algorithms (see Moyo) and contains code for scoring the game.
semeai.c
This file contains semeai()
, the module which tries to
win capturing races. This module does not work particularly
well and will eventually be replaced.
shapes.c
This file containsshapes()
, the module called bygenmove()
which tries to find moves which match a pattern (see Patterns).
showbord.c
This file contains showboard()
, which draws an ASCII
representation of the board, depicting dragons (stones
with same letter) and status (color). This was the
primary interface in GNU Go 1.2, but is now a debugging
aid.
worm.c
This file containsmake_worms()
, code which is run at the beginning of each move cycle, before the code indragon.c
, to determine the attributes of every string. These attributes are things like liberties, wether the string can be captured (and how), etc
utils.c
An assortment of utilities, described in greater detail below.
patterns/
The directory patterns/
contains files related to pattern matching.
Currently there are several types of patterns. A partial list:
patterns.db
and patterns2.db
hoshi.db
etc. which are
automatically build from the files hoshi.sgf
etc. These comprise
our small Joseki library.
owl_attackpats.db
, owl_defendpats.db
and owl_vital_apats.db
. These generate moves for the owl
code (see The Owl Code).
conn.db
(see Connections Database)
influence.db
and barriers.db
(see Influence)
eyes.db
(see Eyes).
The following list contains, in addition to distributed source files
some intermediate automatically generated files such as patterns.c.
These are C source files produced by "compiling" various pattern
databases, or in some cases (such as hoshi.db
) themselves
automatically generated pattern databases produced by "compiling"
joseki files in Smart Go Format.
conn.db
:
Database of connection patterns.
conn.c
:
Automatically generated file, containing connection patterns in form of struct arrays, compiled bymkpat
fromconn.db
.
eyes.c
:
Automatically generated file, containing eyeshape patterns in form of struct arrays, compiled bymkpat
fromeyes.db
.
eyes.h
:
Header file for eyes.c
.
eyes.db
:
Database of eyeshape patterns. See Eyes, for details.
helpers.c
:
These are helper functions to assist in evaluating moves by matchpat.
hoshi.sgf
:
Smart Go Format file containing 4-4 point openings
hoshi.db
:
Automatically generated database of 4-4 point opening
patterns, make by compiling hoshi.sgf
joseki.c
:
Joseki compiler, which takes a joseki file in Smart Go Format, and produces a pattern database.
komoku.sgf
:
Smart Go Format file containing 3-4 point openings
komoku.db
:
Automatically generated database of 3-4 point opening
patterns, make by compiling komoku.sgf
mkeyes.c
:
Pattern compiler for the eyeshape databases. This program takeseyes.db
as input and produceseyes.c
as output.
mkpat.c
:
Pattern compiler for the move generation and connection databases. Takes the filepatterns.db
together with the autogenerated Joseki pattern fileshoshi.db
,komoku.db
,sansan.db
,mokuhadzushi.db
,takamoku.db
and producespatterns.c
, or takesconn.db
and producesconn.c
.
mokuhazushi.sgf
:
Smart Go Format file containing 5-3 point openings
mokuhazushi.db
:
Pattern database compiled from mokuhadzushi.sgf
sansan.sgf
:
Smart Go Format file containing 3-3 point openings
sansan.db
:
Pattern database compiled from sansan.sgf
takamoku.sgf
:
Smart Go Format file containing 5-4 point openings
takamoku.db
:
Pattern database compiled from takamoku.sgf.
patterns.c
:
Pattern data, compiled from patterns.db by mkpat.
patterns.h
:
Header file relating to the pattern databases.
patterns.db
and patterns2.db
:
These contain pattern databases in human readable form.
Please follow the coding conventions at:
<http://www.gnu.org/prep/standards_toc.html
>
Please preface every function with a brief description of its usage.
Please help to keep this Texinfo documentation up-to-date.
A function gprintf()
is provided. It is a cut-down
printf
, supporting only %c
, %d
,
%s
, and without field widths, etc. It does, however,
add some useful facilities:
%m
:
Takes two parameters, and displays a formatted board co-ordinate.
Trace messages are automatically indented to reflect the current stack depth, so it is clear during read-ahead when it puts a move down or takes one back.
format string suppresses the indentation.
A variant mprintf
sends output to stderr. Normally
gprintf()
is wrapped in one of the following:
TRACE(fmt, ...)
:
Print the message if the 'verbose' variable > 0.
(verbose is set by -t
on the command line)
DEBUG(flags, fmt, ...)
:
WhileTRACE
is intended to afford an overview of what GNU Go is considering,DEBUG
allows occasional in depth study of a module, usually needed when something goes wrong.flags
is one of theDEBUG_*
symbols inengine/gnugo.h
. TheDEBUG
macro tests to see if that bit is set in thedebug
variable, and prints the message if it is. The debug variable is set using the-d
command-line option.
The variable verbose
controls the tracing. It
can equal 0 (no trace), 1, 2, 3 or 4 for increasing
levels of tracing. You can set the trace level at
the command line by -t
for verbose=1
,
-t -t
for verbose=2
, etc. But in
practice if you want more verbose tracing than level
1 it is better to use gdb to reach the point where
you want the tracing; you will often find that the
variable verbose
has been temporarily set to zero
and you can use the gdb command set var verbose=1
to turn the tracing back on.
Related to tracing are assertions. Developers are strongly encouraged to pepper their code with assertions to ensure that data structures are as they expect. For example, the helper functions make assertions about the contents of the board in the vicinity of the move they are evaluating.
ASSERT()
is a wrapper around the standard C assert()
function. In addition to the test, it takes an extra pair of parameters
which are the co-ordinates of a "relevant" board position. If an
assertion fails, the board position is included in the trace output, and
showboard()
and popgo()
are called to unwind and display
the stack.
We have adopted the convention of putting the word FIXME in comments to denote known bugs, etc.
If you are using Emacs, you may find it fast and convenient to use
Emacs' built-in facility for navigating the source. Switch to the
root directory gnugo-3.0.x/
and execute the command:
find . -print|grep "\.[ch]$"|xargs etags
This will build a file called gnugo-3.0.x/TAGS
. Now to
find any GNU Go function, type M-.
and enter the
command which you wish to find, or just RET
if
the cursor is at the name of the function sought.
The first time you do this you will be prompted for the location
of the TAGS table. Enter the path to gnugo-3.0.x/TAGS
, and
henceforth you will be able to find any function with a minimum
of keystrokes.
In this chapter we will discuss methods of finding out how GNU Go understands a given position. These methods will be of interest to anyone working on the program, or simply curious about its workings.
We assume that you have a game GNU Go played saved as an sgf file, and you want to know why it made a certain move.
A quick way to find out roughly the reason for a move is to run
gnugo -l filename -t -L move number
(You may also want to add --quiet
to suppress the copyright
message.) In GNU Go 3.0, the moves together with their reasons are
listed, followed by a numerical analysis of the values given to each
move.
If you are tuning (see Tuning) you may want to add the -a
option. This causes GNU Go to report all patterns matched, even ones
that cannot affect the outcome of the move. The reasons for doing
this is that you may want to modify a pattern already matched
instead of introducing a new one.
If you use the -w
option, GNU Go will report the statuses
of dragons around the board. This type of information is available
by different methods, however (see Debugboard, see Colored Display).
If GNU Go is invoked with the option -o filename
it will
produce an output file. This option can be added at the command line
in the Go Modem Protocol Setup Window of CGoban. The output file will
show the locations of the moves considered and their weights. It is
worth noting that by enlarging the CGoban window to its fullest size
it can display 3 digit numbers. Dragons with status DEAD
are
labelled with an X
, and dragons with status CRITICAL
are
labelled with a !
.
If you have a game file which is not commented this way, or which was produced by a non-current version of GNU Go you may ask GNU Go to produce a commented version by running:
gnugo --quiet -l <old file> --replay <color> -o <new file>
Here <color> can be 'black,' 'white' or 'both'. The replay option will also help you to find out if your current version of GNU Go would play differently than the program that created the file.
The --decide-string
option is used to check the tactical reading code
(see Tactical Reading). This option takes an argument, which is a location
on the board in the usual algebraic notation (e.g.
--decide-string C17
). This will tell you whether the reading code (in
engine/reading.c
) believes the string can be captured, and if so,
whether it believes it can be defended, which moves it finds to attack or
defend the move, how many nodes it searched in coming to these
conclusions. Note that when GNU Go runs normally (not with
--decide-string
) the points of attack and defense are
computed when make_worms()
runs and cached in
worm.attack
and worm.defend
.
If used with an output file (-o filename
)
--decide-string
will produce a variation tree showing
all the variations which are considered. This is a useful way
of debugging the reading code, and also of educating yourself
with the way it works. The variation tree can be displayed
graphically using CGoban.
At each node, the comment contains some information. For example you may find a comment:
attack4-B at D12 (variation 6, hash 51180fdf) break_chain D12: 0 defend3 D12: 1 G12 (trivial extension)
This is to be interpreted as follows. The node in question
was generated by the function attack3()
in engine/reading.c
,
which was called on the string at D12
. Of the data in
parentheses tells you the values of count_variations
and
hashdata.hashval
.
The second value ("hash") you probably will not need to know
unless you are debugging the hash code, and we will not discuss it.
But the first value ("variation") is useful when using the debugger
gdb
. You can first make an output file using
the -o
option, then walk through the reading with
gdb
, and to coordinate the SGF file with the debugger,
display the value of count_variations
. Specifically,
from the debugger you can find out where you are as follows:
(gdb) set dump_stack() B:D13 W:E12 B:E13 W:F12 B:F11 (variation 6)
If you place yourself right after the call to trymove()
which generated the move in question, then the variation number
in the SGF file should match the variation number displayed by
dump_stack()
, and the move in question will be the
last move played (F11 in this example).
This displays the sequence of moves leading up to the variation
in question, and it also prints count_variations-1
.
The second two lines tell you that from this node, the function
break_chain()
was called at D12 and returned 0 meaning
that no way was found of rescuing the string by attacking
an element of the surrounding chain, and the function
defend3()
was called also at D12 and returned 1,
meaning that the string can be defended, and that
G12 is the move that defends it. If you have trouble
finding the function calls which generate these comments,
try setting sgf_dumptree=1
and setting a breakpoint in
sgf_trace
.
You can similarly debug the Owl code using the option
--decide-dragon
. Usage is entirely similar to
--decide-string
, and it can be used similarly
to produce variation trees. These should be typically
much smaller than the variation trees produced by
--decide-string
.
You can use the Go Text Protocol (see GTP) to determine
the statuses of dragons and other information needed for
debugging. The GTP command dragon_data P12
will list
the dragon data of the dragon at P12
and
worm_data
will list the worm data; other GTP
commands may be useful as well.
You can also conveniently get such information from GDB.
A suggested .gdbinit
file may be found in
See Debugging. Assuming this file is loaded, you can
list the dragon data with the command:
(gdb) dragon P12
Similarly you can get the worm data with worm P12
.
A useful utility called debugboard
is made in
the interface/debugboard/
directory. This can be run
in an Xterm. Use a smaller font since it requires 50 rows
and 80 columns. This runs examine_position()
, then
makes a graphical display of the board. Using the cursor
movement keys, you can move around the board and find
out the contents of the worm, dragon and eye arrays.
GNU Go can score the game. If done at the last move, this is usually
accurate unless there is a seki. Normally GNU Go will report its
opinion about the score at the end of the game, but if you want this
information about a game stored in a file, use the --score
option.
gnugo --score last -l filename
loads the sgf file to the end of the file and estimates the winner after the last stored move by estimating the territory.
gnugo --score end -l filename
loads the sgf file and GNU Go continues to play after the last stored move by itself up to the very end. Then the winner is determined by estimating the territory.
gnugo --score aftermath -l filename
loads the sgf file and GNU Go continues to play after the last stored
move by itself up to the very end. Then the winner is determined by
the most accurate algorithm available. Slower but more accurate than
--score end
.
gnugo --score L10 -l filename
loads the sgf file until a stone is placed on L10. Now the winner will
be estimated as with gnugo --score last
.
Any of these commands may be combined with --chinese-rules
if you want to use Chinese (area) counting.
gnugo --score 100 -l filename
loads the sgf file until move number 100. Now the winner will be estimated
as with gnugo --score last
.
If the option -o outputfilename
is provided, the results
will also be written as comment at the end of the output file.
Various colored displays of the board may be obtained in a color
xterm
or rxvt
window. Xterm will only work if xterm is not
compiled with color support. If the colors are not displayed on your xterm,
try rxvt
. You may also use the Linux console. The colored display
will work best if the background color is black; if this is not the case you
may want to edit your .Xdefaults
file or add the options
-bg black -fg white
to xterm
or rxvt
.
You can get a colored ASCII display of the board in which each dragon
is assigned a different letter; and the different matcher_status
values
(ALIVE
, DEAD
, UNKNOWN
, CRITICAL
) have different
colors. This is very handy for debugging. Actually two diagrams are generated.
The reason for this is concerns the way the matcher status is computed.
The dragon_status (see Dragons) is computed first, then for some, but not
all dragons, a more accurate owl status is computed. The matcher status is
the owl status if available; otherwise it is the dragon_status. Both the
dragon_status and the owl_status are displayed. The color scheme is as
follows:
green = alive cyan = dead red = critical yellow = unknown magenta = unchecked
To get the colored display, save a game in sgf format using CGoban, or using
the -o
option with GNU Go itself.
Open an xterm
or rxvt
window.
Execute gnugo -l [filename] -L [movenum] -T
to get the colored
display.
Other useful colored displays may be obtained by using instead:
Instead of -T
, try this with -E
. This gives a colored
display of the eyespaces, with marginal eye spaces marked !
(see Eyes).
The option -m level
can give colored displays of the
various quantities which are computed in engine/moyo.c
.
The moyos found by GNU Go can be displayed from an xterm or rxvt window or
from the Linux console using the -m
option. This takes a parameter:
-m level
use or (hexadecimal) cumulative values for printing these reports :
1 0x01 ascii printing of territorial evaluation (5/21)
2 0x02 ascii printing of moyo evaluation (5/10)
4 0x04 ascii printing of area (4/0)
8 0x08 print initial moyo influence
16 0x10 print influence
32 0x20 numeric influence
64 0x40 moyo strength
128 0x80 moyo attenuation
The first three options are somewhat superceded because these data are no longer used by the engine.
These options can be combined by adding the levels. Levels
16, 32, 64 and 128 don't do much unless you also specify level 8.
Thus one might use the hexadecimal option -m0x018
if you
want to see the influence function displayed graphically.
See Moyo, for the first three items.
See Influential Display, for the last five items.
If you want to write your own interface to GNU Go, or if you want to create a go application using the GNU Go engine, this chapter is of interest to you.
First an overview: GNU Go consists of two parts: the GNU Go engine and a program (user interface) which uses this engine. These are linked together into one binary. The current program implements the following user modes:
The GNU Go engine can be used in other applications. For example, supplied
with GNU Go is another program using the engine, called debugboard
,
in the directory interface/debugboard/
. The program debugboard lets the
user load SGF files and can then interactively look at different properties of
the position such as group status and eye status.
The purpose of this Chapter is to show how to interface your own
program such as debugboard
with the GNU Go engine.
Figure 1 describes the structure of a program using the GNU Go engine.
+-----------------------------------+ | | | Go application | | | +-----+----------+------+ | | | | | | | | Game | | | | | handling | | | | | | | | | +----+-----+ | | | SGF | Move | | | handling | generation | | | | | | +----------+------------+-----------+ | | | Board handling | | | +-----------------------------------+ Figure 1: The structure of a program using the GNU Go engine
The foundation is a library called libboard.a
which provides
efficient handling of a go board with rule checks for moves, with
incremental handling of connected strings of stones and with methods to
efficiently hash go positions.
On top of this, there is a library which helps the application use
smart go files, SGF files, with complete handling of game trees in
memory and in files. This library is called libsgf.a
The main part of the code within GNU Go is the move generation
library which given a position generates a move. This part of the
engine can also be used to manipulate a go position, add or remove
stones, do tactical and strategic reading and to query the engine for
legal moves. These functions are collected into libengine.a
.
The game handling code helps the application programmer keep tracks
of the moves in a game, and to undo or redo moves. Games can be saved to
SGF files and then later be read back again. These are also within
libengine.a
.
The resposibility of the application is to provide the user with a user interface, graphical or not, and let the user interact with the engine.
To use the GNU Go engine in your own program you must include
the file gnugo.h
. This file describes the whole public API. There is
another file, liberty.h
, which describes the internal interface within
the engine. If you want to make a new module within the engine, e.g. for
suggesting moves you will have to include this file also. In this section we
will only describe the public interface.
Before you do anything else, you have to call the function
init_gnugo()
. This function initializes everything within the engine.
It takes one parameter: the number of megabytes the engine can use for
the internal hash table. In addition to this the engine will use a few
megabytes for other purposes such as data describing groups (liberties,
life status, etc), eyes and so on.
There are some basic definitions in gnugo.h which are used everywhere. The most important of these are the numeric declarations of colors. Each intersection on the board is represented by one of these:
color value EMPTY 0 WHITE 1 BLACK 2
In addition to these, the following values can be used in special places, such as describing the borders of eyes:
color value GRAY (GRAY_BORDER) 3 WHITE_BORDER 4 BLACK_BORDER 5
There is a macro, OTHER_COLOR(color)
which can be used to get the
other color than the parameter. This macro can only be used on WHITE
or BLACK
, but not on EMPTY
or one of the border colors.
The basic data structure in the interface to the engine is the
Position
. A Position
is used to store the current position
of a game including the location of all black and white stones, a
possible ko, and the number of captured stones on each side. Here is
the definition of Position
:
typedef unsigned char Intersection; typedef struct { int boardsize; Intersection board[MAX_BOARD][MAX_BOARD]; int ko_i; int ko_j; int last_i[2]; int last_j[2]; float komi; int white_captured; int black_captured; } Position;
Here Intersection
stores EMPTY
, WHITE
or
BLACK
. It is currently defined as an unsigned char
to make
it reasonably efficient in both storage and access time. The position
stores a two-dimensional array of Intersections with the size
MAX_BOARD
. MAX_BOARD
is the value of the biggest board
size that the engine supports; it is currently set to 21. There is also
a MIN_BOARD
which is set to 3.
To indicate what board size is actually used, there is a member,
boardsize
, which should be in the range between MIN_BOARD
and MAX_BOARD
.
A location on the board is represented by a pair of integers in the range
[0 ... boardsize-1]
. The convention used within GNU Go is that the
first integer indicates the row number from the top and the second integer
indicates the column number from the left. Thus the coordinate (2,5) is F5 (A)
in the small diagram below.
A B C D E F G 7 . . . . . . . 7 6 . . . . . . . 6 5 . . . . . A . 5 4 . . . . . . . 4 3 . . . . . . . 3 2 . . . . . . . 2 1 . . . . . . . 1 A B C D E F G
A pass move is represented by the pair (-1,-1)
. A convention
within the code is to use the suffix i
and j
for the first and
the last coordinate.
If there is a ko present on the board, that is if one stone was
captured the last move and the capturing stone can be recaptured, the
pair (ko_i, ko_j)
points at the empty intersection where the stone was
just captured (a
in the diagram below).
A B C D E F G 7 . . . . . . . 7 6 . . . . . . . 6 5 . . . O X . . 5 4 . . O a O X . 4 3 . . . O X . . 3 2 . . . . . . . 2 1 . . . . . . . 1 A B C D E F G
If no ko is present, ko_i
should be set to -1
.
The last two moves played are stored in (last_i[], last_j[])
.
As the game progresses the number of prisoners on each side are
maintained in the members white_captured
and black_captured
.
The komi used in the ongoing game is also stored in the Position
.
The reason for this is that in some instances, GNU Go plays differently
whether it is ahead, behind or the position is even. So the komi is an
important input to the move generation.
All the functions in the engine that manipulate Positions have names
prefixed by gnugo_
. Here is a complete list, as defined in
gnugo.h
:
void gnugo_clear_position(Position *pos, int boardsize, float komi)
Clear the position setting the board size toboardsize
and the komi tokomi
.
void gnugo_copy_position(Position *dest, Position *src)
Copy positionsrc
to positiondest
. This is the same convention that is used inmemcpy(3)
.
void gnugo_add_stone(Position *pos, int i, int j, int color)
Add a stone ofcolor
at(i,j)
to the position.
void gnugo_remove_stone(Position *pos, int i, int j)
Remove the stone at (i,j)
from the position. No check is
done that there actually is a stone there.
void gnugo_play_move(Position *pos, int i, int j, int color)
Play a stone of color color at(i, j)
in the position removing captured stones if any. No check is done if the move is legal; to do that, callgnugo_is_legal()
. Suicide is legal.
int gnugo_play_sgfnode(Position *pos, SGFNode *node, int to_move)
Place all the stones in and play all the moves in the SGF node
node
(see SGF.) Return whose turn it is to move after this is
done.
int gnugo_play_sgftree(Position *pos, SGFNode *root, int *until, SGFNode **curnode)
Clear the position and play through the moves in SGF treeroot
until the move numberuntil
has been reached. Return whose turn it is to move after this is done. The parametercurnode
will be set to the current node in the tree, i.e. the one which was played last.
int gnugo_is_legal(Position *pos, int i, int j, int color)
Return 1 if the move at(i,j)
would be legal; otherwise return 0. The rule set used is standard japanese rules where suicide is illegal. If there is a ko point set (ko_i != -1
), then the ko point is also illegal to play on.
int gnugo_is_suicide(Position *pos, int i, int j, int color)
Return 1 if the move at (i,j)
would be suicide; otherwise return 0.
int gnugo_placehand(Position *pos, int handicap)
Sets up handicap stones, returning the number of placed handicap stones. Maximum handicap supported is 0 for board sizes below 7, 4 for board sizes 7 or 8 and 9 for board sizes from 9 and up.
int gnugo_sethand(Position *pos, int handicap, struct SGFNode_t *root)
Sets up handicap pieces and returns the number of placed handicap stones, updating the SGF file.
void gnugo_recordboard(Position *pos, struct SGFNode_t *node)
Records the position in the SGF node (see SGF).
int gnugo_genmove(Position *pos, int *i, int *j, int color, int move_number)
Generate a move for colorcolor
and return it in(*i,*j)
. The parametermove_number
is the number of the current move. This is mostly used for debugging reasons, as the game handling functions all work on top of the move generation part of the engine. (see Move Generation Basics.).
float gnugo_estimate_score(Position *pos, float *upper, float *lower)
Evaluate the approximate score. The score is given as an interval with a lower and upper bound. A positive score means that white is leading, while a negative score is good for black. When the lower bound is estimated, CRITICAL dragons are awarded to white; when estimating the lower bound, they are awarded to black.The estimation is returned through the pointers
*upper
and*lower
, and the mean between them is returned as the functions value.
void gnugo_who_wins(Position *pos, int color, FILE *outfile)
Score the game and determine the winner.
These functions examines the position in different ways and tells the status of groups and other items.
int gnugo_attack(Position *pos, int m, int n, int *i, int *j)
Calls the tactical reading functionattack
to determine whether the string at(m, n)
can be captured (see Tactical Reading).
int gnugo_find_defense(Position *pos, int m, int n, int *i, int *j)
Calls the tactical reading functionfind_defense
to determine whether the string at(m, n)
can be rescued (see Tactical Reading).
These functions are only used in special situations, such as when the program wants to access internal data structures within the engine. They should only be used when the programmer has a good knowledge of the internals of GNU Go.
void gnugo_force_to_globals(Position *pos)
Put the values inpos
into the global variables which is the equivalent of thePosition
.
void gnugo_examine_position(Position *pos, int color, int how_much)
Calls examine_position()
, doing much prelimary analysis of
the board position (see Move Generation Basics).
The functions (in see Positional Functions) are all that are needed to create a fully functional go program. But to make the life easier for the programmer, there is a small set of functions specially designed for handling ongoing games.
The data structure describing an ongoing game is the Gameinfo
. It
is defined as follows:
typedef struct { int handicap; Position position; int move_number; int to_move; /* whose move it currently is */ SGFTree moves; /* The moves in the game. */ int seed; /* random seed */ int computer_player; /* BLACK, WHITE, or EMPTY (used as BOTH) */ char outfilename[128]; /* Trickle file */ FILE *outfile; } Gameinfo;
The meaning of handicap
should be obvious. The position
field is of course the current position, move_number
is the
number of the current move and to_move
is the color of the side
whose turn it is to move.
The SGF tree moves
is used to store all the moves in the entire
game, including a header node which contains, among other things, komi
and handicap. If a player wants to undo a move, this can most easily be
done by replaying all the moves in the tree except for the last
one. This is the way it is implemented in gameinfo_undo_move()
.
If one or both of the opponents is the computer, the fields seed
and computer_player
are used. Otherwise they can be
ignored. seed
is used to store the number used to seed the random
number generator. Given the same moves from the opponent, GNU Go will
try to vary its game somewhat using a random function. But if the random
generator is given the same seed, GNU Go will always play the same
move. This is good, e.g. when we debug the engine but could also be used
for other purposes.
GNU Go can use a trickle file to continuously save all the moves of an
ongoing game. This file can also contain information about internal
state of the engine such as move reasons for various locations or move
valuations for the 10 highest valued moves. The name of this file should
be stored in outfilename
and the file pointer to the open file is
stored in outfile
. If no trickle file is used,
outfilename[0]
will contain a null character and outfile
will be set to NULL
.
All the functions in the engine that manipulate Gameinfos have names
prefixed by gameinfo_
. Here is a complete list, as defined in
gnugo.h
:
void gameinfo_clear(Gameinfo *ginfo, int boardsize, float komi)
Clear the Gameinfo to an empty state. The board size of thePosition
is set toboardsize
.
void gameinfo_print(Gameinfo *ginfo)
Print the Gameinfo on stdout. This is mostly a debug tool.
void gameinfo_load_sgfheader(Gameinfo *ginfo, SGFNode *head)
Load header information from the SGF nodehead
and set the appropriate variables inginfo
.
void gameinfo_play_move(Gameinfo *ginfo, int i, int j, int color)
Play a move at (i
,j
), record it inmoves
, print it to the trickle file if any and updatemove_number
andto_move
.
void gameinfo_undo_move(Gameinfo *ginfo)
Replays all the moves of the game except the last one. It also updatesmove_number
,to_move
andmoves
. If there is a trickle file, it is truncated to the second to last move.FIXME: Not yet implemented.
int gameinfo_play_sgftree(Gameinfo *ginfo, SGFNode *head,
const char *untilstr)
Read header information and play the main variation in the SGF tree starting withhead
. Return whose turn it is to move after this is done.The parameter
untilstr
is an optional string of the form 'L12' (a board position) or '120' (a move number) which tells the function to stop playing at that move or move number.
SGF - Smart Game Format - is a file format which is used for storing
game records for a number of different games, among them chess and
go. The format is a framework with special adaptions to each game. This
is not a description of the file format standard. Too see the exact
definition of the file format, see <http://www.red-bean.com/sgf/
>.
GNU Go contains a library to handle go game records in the SGF format in
memory and to read and write SGF files. This library - libsgf.a
-
is in the sgf
subdirectory. To use the SGF routines, include the
file sgftree.h
.
Each game record is stored as a tree of nodes, where each node represents a state of the game, often after some move is made. Each node contains zero or more properties, which gives meaning to the node. There can also be a number of child nodes which are different variations of the game tree. The first child node is the main variation.
Here is the definition of SGFNode
, and SGFProperty
, the
data structures which are used to encode the game tree.
typedef struct SGFProperty_t { struct SGFProperty_t *next; short name; char value[1]; } SGFProperty; typedef struct SGFNode_t { SGFProperty *props; struct SGFNode_t *parent; struct SGFNode_t *child; struct SGFNode_t *next; } SGFNode;
Each node of the SGF tree is stored in an SGFNode
struct. It has
a pointer to a linked list of properties (see below) called
props
. It also has a pointer to a linked list of children, where
each child is a variation which starts at this node. The variations are
linked through the next
pointer and each variation continues
through the child
pointer. Each and every node also has a pointer
to its parent node (the parent
field), except the top node whose
parent pointer is NULL
.
An SGF property is encoded in the SGFPoperty
struct. It is linked
in a list through the next
field. A property has a name
which is encoded in a short int. Symbolic names of properties can be
found in sgf_properties.h
.
Some properties also have a value, which could be an integer, a floating point value, a character or a string. These values can be accessed or set through special functions (see below).
All the functions which create and manipulate SGF trees are prefixed by
sgf
. The SGF code was donated to us by Thomas Traber, so they
don't follow the naming conventions of GNU Go perfectly.
These functions let the caller create nodes or access nodes easier.
SGFNode *sgfNewNode(void)
Allocate and return a new instance of SGFNode
. The node is
cleared.
SGFProperty *sgfMkProperty(const char *name, const char *value,
SGFNode *node, SGFProperty *last)
Allocate and return a new instance ofSGFProperty
. Thename
should be 1 or 2 characters long. This function should probably not be used directly. Instead, use thesgfAddProperty
functions.
SGFNode *sgfPrev(SGFNode *node)
Return the previous node in a chain. This is done by going to the parent
node and then search through the children until the same node is found.
If there is no previous node, NULL
is returned.
SGFNode *sgfRoot(SGFNode *node)
Return the root of the tree. Ifnode
already is the root,node
itself is returned.
int sgfGetIntProperty(SGFNode *node, const char *name, int
*value)
Get the propertyname
innode
as an integer. The value is returned invalue
. Returns 1 if successful, otherwise returns 0.
int sgfGetFloatProperty(SGFNode *node, const char *name,
float *value)
Get the propertyname
innode
as a floating point value. The value is returned invalue
. Returns 1 if successful, otherwise returns 0.
int sgfGetCharProperty(SGFNode *node, const char *name, char
**value)
Get the propertyname
innode
as a string of characters. The value is returned invalue
. Returns 1 if successful, otherwise returns 0.
void sgfAddProperty(SGFNode *node, const char *name, const
char *value)
Add a new property to node
. There is no check to see if there
already is a property with the same name. The property value has to be a
character string.
void sgfAddPropertyInt(SGFNode *node, const char *name, long
val)
Add an integer property tonode
. This function converts the value to a string and callssgfAddProperty
.
void sgfAddPropertyFloat(SGFNode *node, const char *name,
float val)
Add a floating point property tonode
. This function converts the value to a string and callssgfAddProperty
.
void sgfOverwriteProperty(SGFNode *node, const char *name,
const char *text)
Overwrite the propertyname
innode
with the stringtext
. If the property does not yet exist innode
, it is added usingsgfAddProperty
.
void sgfOverwritePropertyInt(SGFNode *node, const char
*name, int value)
Overwrite the propertyname
innode
with the integervalue
. If the property does not yet exist innode
, it is added usingsgfAddPropertyInt
.
void sgfOverwritePropertyFloat(SGFNode *node, const char
*name, float value)
Overwrite the propertyname
innode
with the floating point numbervalue
. If the property does not yet exist innode
, it is added usingsgfAddPropertyFloat
.
SGFNode *sgfAddStone(SGFNode *node, int color, int movex,
int movey)
Add a stone tonode
. Properties added is eitherAB
(black stone) orAW
(white stone).
SGFNode *sgfAddPlay(SGFNode *node, int who, int movex, int
movey)
Add a child node with a move tonode
. Properties added is eitherB
(black move) orW
(white move). A pass is coded by(-1, -1)
.This function does not add a property to the node itself, but adds a child node instead. If there are previous child nodes, the new node is placed before the other ones, so this function should be used if you want to add a main branch to the tree. To add a variation, use
sgfAddPlayLast
instead.
SGFNode *sgfAddPlayLast(SGFNode *node, int who, int movex,
int movey)
Add a child node with a move tonode
. Properties added is eitherB
(black move) orW
(white move). A pass is coded by(-1, -1)
.If there are previous child nodes in
node
, the move is added by adding the child node last, so this function should be used when you want to add a variation to the game tree.
int sgfPrintCharProperty(FILE *file, SGFNode *node, const
char *name)
Print the properties of typename
innode
onfile
.
int sgfPrintCommentProperty(FILE *file, SGFNode *node, const
char *name)
Print the comment properties of typename
innode
onfile
.
void sgfWriteResult(SGFNode *node, float score, int
overwrite)
Add aRE
(result) property tonode
. This property will contain the game result. Ifoverwrite
is zero the result is written only if no previous result property exists.
SGFNode *sgfCircle(SGFNode *node, int i, int j)
Add aCR
(circle) property at(i, j)
tonode
.
SGFNode *sgfSquare(SGFNode *node, int i, int j)
CallssgfMark
to add aMA
(mark) property at(i, j)
tonode
.
SGFNode *sgfTriangle(SGFNode *node, int i, int j)
Add aTR
(triangle) property at(i, j)
tonode
.
SGFNode *sgfMark(SGFNode *node, int i, int j)
Add aMA
(mark) property at(i, j)
tonode
.
SGFNode *sgfAddComment(SGFNode *node, const char *comment)
Add aC
(comment) property tonode
.
SGFNode *sgfBoardText(SGFNode *node, int i, int j, const
char *text)
Add aLB
(label) property at(i, j)
tonode
.
SGFNode *sgfBoardChar(SGFNode *node, int i, int j, char c)
Add aLB
(label) property at(i, j)
tonode
. This functions is a utility function that converts the character to a string and callssgfBoardText
.
SGFNode *sgfBoardNumber(SGFNode *node, int i, int j, int
number)
Add a numeric label at(i, j)
by callingsgfBoardText
.
SGFNode *sgfStartVariant(SGFNode *node)
Start a new variation in the game tree. This means that thenext
pointer ofnode
is followed to the end of the list and a new node is inserted there. A pointer to the new node is returned.
SGFNode *sgfStartVariantFirst(SGFNode *node)
Same as sgfStartVariant
, except that the node is placed first in
the list. This means that the new variation will be the main variation
of the game tree. Returns a pointer to the new node.
SGFNode *sgfAddChild(SGFNode *node)
Adds a child node to node
. If there already are children, the new
node is placed last in the list. Returns a pointer to the new node.
SGFNode *sgfCreateHeaderNode(int boardsize, float komi)
Create a new SGF node with the two propertiesSZ
(size) andKM
(komi). More properties, likeHA
(handicap), can later be added to it.The idea with this node is to store the game info and to use as a root node for the game.
SGFNode *readsgffile(const char *filename)
Read an SGF file and return the resulting tree.
void sgf_write_header(SGFNode *root, int overwrite, int
seed, float komi)
Write random seed, date, ruleset, komi and SGF file version to the header noderoot
. Ifoverwrite
is non-zero, it overwrites the values in the node, otherwise it just writes those that are missing.Ruleset is always set to "Japanese", date is set to the current date.
int writesgf(SGFNode *root, const char *filename)
Write the tree starting inroot
to the filefilename
. Iffilename
is-
, the tree is written tostdout
. Returns 1 if successful, otherwise returns 0.
Sometimes we just want to record an ongoing game or something similarly
simple and not do any sofisticated tree manipulation. In that case we
can use the simplified interface provided by SGFTree
below.
typedef struct SGFTree_t { SGFNode *root; SGFNode *lastnode; } SGFTree;
An SGFTree
contains a pointer to the root node of an SGF tree and
a pointer to the node that we last accessed. Most of the time this will
be the last move of an ongoing game.
Most of the functions which manipulate an SGFTree
work exactly
like their SGFNode
counterparts, except that they work on the
current node of the tree.
All the functions below that take arguments tree
and node
will work on:
node
if non-NULL
tree->lastnode
if non-NULL
void sgftree_clear(SGFTree *tree)
Clear theroot
andlastnode
pointers oftree
.NOTE:
This function does not free any memory. That has to be done separately.
int sgftree_readfile(SGFTree *tree, const char *infilename)
Read an SGF file with the nameinfilename
and store it intree
. Return 1 if successful, otherwise return 0.lastnode
will be set toNULL
.
SGFNode *sgftreeNodeCheck(SGFTree *tree, SGFNode *node)
Return the node to work on as described above. This is:in that order.
node
if non-NULL
tree->lastnode
if non-NULL
- The current end of the tree.
SGFNode *sgftreeAddPlay(SGFTree *tree, SGFNode *node, int
color int movex, int movey)
Add a move ofcolor
at(movex,movey)
to the tree. See sgfAddPlay.
SGFNode *sgftreeAddPlayLast(SGFTree *tree, SGFNode *node,
int color, int movex, int movey)
Add a variation ofcolor
at(movex,movey)
to the tree. See sgfAddPlayLast.
SGFNode *sgftreeAddStone(SGFTree *tree, SGFNode *node, int
color, int movex, int movey)
Add a stone ofcolor
at(movex,movey)
to the tree.
void sgftreeWriteResult(SGFTree *tree, float score, int
overwrite)
Add the result to the tree. If there already is a result, only overwrite
it if overwrite
is non-zero.
SGFNode *sgftreeCircle (SGFTree *tree, SGFNode *node, int
i, int j)
Add a circle property at (i, j)
to the tree.
SGFNode *sgftreeSquare (SGFTree *tree, SGFNode *node, int
i, int j)
Add a square property at (i, j)
to the tree.
SGFNode *sgftreeTriangle(SGFTree *tree, SGFNode *node, int
i, int j)
Add a triangle property at (i, j)
to the tree.
SGFNode *sgftreeMark(SGFTree *tree, SGFNode *node, int i, int j)
Add a mark property at (i, j)
to the tree.
SGFNode *sgftreeAddComment(SGFTree *tree, SGFNode *node,
const char *comment)
Add a comment property to the tree. This is a property of the node itself, and has no position on the board.
SGFNode *sgftreeBoardText(SGFTree *tree, SGFNode *node, int
i, int j, const char *text)
Add a text property at (i, j)
to the tree.
SGFNode *sgftreeBoardChar(SGFTree *tree, SGFNode *node, int
i, int j, char c)
Add a character at (i, j)
to the tree.
SGFNode *sgftreeBoardNumber(SGFTree *tree, SGFNode *node,
int i, int j, int number)
Add a number at (i, j)
to the tree.
SGFNode *sgftreeStartVariant(SGFTree *tree, SGFNode *node)
Start a new variation in the tree. See sgfStartVariant.
SGFNode *sgftreeStartVariantFirst(SGFTree *tree, SGFNode
*node)
Start a new main variation in the tree. See sgfStartVariantFirst.
SGFNode *sgftreeCreateHeaderNode(SGFTree *tree, int
boardsize, float komi)
Add a header node first in tree
.
void sgftreeSetLastNode(SGFTree *tree, SGFNode
*last_node)
Explicitly set the last accessed node intree
tolast_node
.
The foundation of the GNU Go engine is a library of very efficient
routines for handling go boards. This board library, called
libboard
, can be used for those programs that only need a
basic go board but no AI capability. One such program is
patterns/joseki
subdirectory, which compiles joseki pattern
databases from SGF files.
The library consists of the following files:
board.c
The basic board code. It uses incremental algorithms for keeping track of strings and liberties on the go board.
hash.c
Code for hashing go positions.
cache.c
Code for caching go positions
globals.c
Global variables needed in the rest of the files. This file also contains global variables needed in the rest of the engine.
sgffile.c
Implementation of output file in SGF format.
showbord.c
Print go boards.
printutils.c
Utilities for printing go boards and other things.
To use the board library, you must include liberty.h
just like
when you use the whole engine, but of course you cannot use all the
functions declared in it, i.e. the functions that are part of the
engine, but not part of the board library. You must link your
application with libboard.a
.
The basic data structures of the board correspond tightly to the
Position
struct described in See The Position Struct. They are all
stored in global variables for efficiency reasons, the most important of which
are:
int board_size; Intersection p[MAX_BOARD][MAX_BOARD]; int board_ko_i; int board_ko_j; int last_moves_i[2]; int last_moves_j[2]; float komi; int white_captured; int black_captured; Hash_data hashdata;
The description of the Position
struct is applicable to these
variables also, so we won't duplicate it here. All these variables are
globals for performance reasons. Behind these variables, there are a
number of other private data structures. These implement incremental
handling of strings, liberties and other properties
(see Incremental Board). The variable hashdata
contains information
about the hash value for the current position (see Hashing).
These variables should never be manipulated directly, since they are only the front end for the incremental machinery. They can be read, but should only be written by using the functions described in the next section. If you write directly to them, the incremental data structures will become out of sync with each other, and a crash is the likely result.
These functions are all the public functions in engine/board.c
.
These functions are used when you want to set up a new position without actually playing out moves.
void clear_board()
Clears the internal board (p[][]
), resets the ko position,
captured stones and recalculates the hash value.
void setup_board(Intersection new_p[MAX_BOARD][MAX_BOARD], int koi, int koj, int *last_i, int *last_j, float new_komi, int w_captured, int b_captured)
Set up a new board position using the parameters.
void add_stone(int i, int j, int color)
Place a stone on the board and update the hashdata. No captures are done.
void remove_stone(int i, int j)
Remove a stone from the board and update the hashdata.
Reading, often called search in computer game
theory, is a fundamental process in GNU Go. This is the process
of generating hypothetical future boards in order to determine
the answer to some question, for example "can these stones live."
Since these are hypothetical future positions, it is important
to be able to undo them, ultimately returning to the present
board. Thus a move stack is maintained during reading. When
a move is tried, by the function trymove
, or its
variant tryko
. This function pushes the current board
on the stack and plays a move. The stack pointer stackp
,
which keeps track of the position, is incremented. The function
popgo()
pops the move stack, decrementing stackp
and
undoing the last move made.
Every successful trymove()
must be matched with a popgo()
.
Thus the correct way of using this function is:
if (trymove(i, j, color, [message], k, l, komaster, kom_i, kom_j)) { ... [potentially lots of code here] popgo(); }
Here the komaster
is only set if a conditional ko capture has been made
at an earlier move. This feature of the tactical and owl reading code in GNU
Go is used to prevent redundant reading when there is a ko on the board
(see Ko). If komaster is not defined then take the last three parameters
to be EMPTY
, and -1, -1
.
void play_move(int i, int j, int color)
Play a move at(i, j)
. If you want to test for legality you should first callis_legal()
. This function strictly follows the algorithm:
1. Place a stone of given color on the board.
2. If there are any adjacent opponent strings without liberties, remove them and increase the prisoner count.
3. If the newly placed stone is part of a string without liberties, remove it and increase the prisoner count.
int trymove(int i, int j, int color, const char *message, int k, int l, int komaster, int kom_i, int kom_j)
Returns true if(i,j)
is a legal move forcolor
. In that case, it pushes the board on the stack and makes the move, incrementingstackp
. If the reading code is recording reading variations (as with--decide-string
or with-o
), the string*message
will be inserted in the SGF file as a comment. The comment will also refer to the string at(k,l)
if these are not(-1,-1)
.
int TRY_MOVE()
Wrapper around trymove which suppresses*message
and(k,l)
. Used inhelpers.c
int tryko(int i, int j, int color, const char *message, int komaster, kom_i, kom_j)
tryko()
pushes the position onto the stack, and makes a move(i, j)
ofcolor
. The move is allowed even if it is an illegal ko capture. It is to be imagined thatcolor
has made an intervening ko threat which was answered and now the continuation is to be explored. Return 1 if the move is legal with the above caveat. Returns zero if it is not legal because of suicide.
void popgo()
Pops the move stack. This function must (eventually) be called after a succesfultrymove
ortryko
to restore the board position. It undoes all the changes done by the call totrymove/tryko
and leaves the board in the same state as it was before the call.NOTE: If
trymove/tryko
returns0
, i.e. the tried move was not legal, you must not callpopgo
.
int komaster_trymove(int i, int j, int color,
const char *message, int si, int sj,
int komaster, int kom_i, int kom_j,
int *new_komaster, int *new_kom_i, int *new_kom_j,
int *is_conditional_ko, int consider_conditional_ko)
Variation oftrymove
/tryko
where ko captures (both conditional and unconditional) must follow a komaster scheme (see Ko).
int move_in_stack(int m, int n, int cutoff)
Returns true if at least one move been played at (m, n)
at deeper than level 'cutoff' in the reading tree.
void get_move_from_stack(int k, int *i, int *j, int *color)
Retrieve the move numberk
from the move stack. The move location is returned in(*i, *j)
, and the color that made the move is returned in*color
.
void dump_stack(void)
Handy for debugging the reading code under GDB. Prints the move stack.
Usage: (gdb) set dump_stack()
.
void reset_trymove_counter()
Reset the trymove counter. This counter is incremented every time that a variant oftrymove
ortryko
is called.
int get_trymove_counter()
Retrieve the trymove counter.
These functions are used for inquiring about properties of the current position or of potential moves.
int is_pass(int i, int j)
Returns true if the move(i,j)
is a pass move, i.e.(-1, -1)
.
int is_legal(int i, int j, int color)
Returns true if a move at(i,j)
is legal forcolor
.
int is_ko(int m, int n, int color, int *ko_i, int *ko_j)
Return true if the move(i,j)
bycolor
is a ko capture whether capture is a legal ko capture on this move or not. If(*ko_i,*ko_j)
are non-NULL
, then the location of the captured ko stone are returned through(*ko_i,*ko_j)
. If the move is not a ko capture,(*ko_i,*ko_j)
is set to(-1, -1)
.
int is_illegal_ko_capture(int i, int j, int color)
Return true if the move(i,j)
bycolor
would be an illegal ko capture. There is no need to call bothis_ko
andis_illegal_ko_capture
.
int is_self_atari(int i, int j, int color)
Return true if a move bycolor
at(i, j)
would be a self atari, i.e. whether it would get only one liberty. This function returns true also for the case of a suicide move.
int is_suicide(int i, int j, int color)
Returns true if a move at(i,j)
is suicide forcolor
.
int does_capture_something(int i, int j, int color)
Returns true if a move at (i,j)
does capture any stone for the
other side.
int stones_on_board(int color)
Return the number of stones of the indicated color(s) on the board. This only count stones in the permanent position, not stones placed bytrymove()
ortryko()
. Usestones_on_board(BLACK | WHITE)
to get the total number of stones on the board.
These functions are used for getting information like liberties, member stones and similar about strings. Most of these are here because they have a particularly efficient implementation through access to the incremental data structures behind the scene.
void find_origin(int i, int j, int *origini, int *originj)
Find the origin of a worm or a cavity, i.e. the point with smallesti
coordinate and in the case of a tie with smallestj
coordinate. The idea is to have a canonical reference point for a string.
int findstones(int m, int n, int maxstones, int *stonei, int *stonej)
Find the stones of the string at(m, n)
.(m, n)
must not be empty. The locations of up tomaxstones
stones are written into(stonei[], stonej[])
. The full number of stones is returned.
int countstones(int m, int n)
Count the number of stones in a string.
void mark_string(int i, int j, char mx[MAX_BOARD][MAX_BOARD], char mark)
For each stone in the string at(i, j)
, setmx
to valuemark
. If some of the stones in the string are marked prior to calling this function, only the connected unmarked stones starting from(i, j)
are guaranteed to become marked. The rest of the string may or may not become marked.
int liberty_of_string(int ai, int aj, int si, int sj)
Returns true if(ai, aj)
is a liberty of the string at(si, sj)
.
int neighbor_of_string(int ai, int aj, int si, int sj)
Returns true if(ai, aj)
is adjacent to the string at(si, sj)
.
int same_string(int ai, int aj, int bi, int bj)
Returns true if(ai, aj)
is a stone in the same string as(bi, bj)
.
int findlib(int m, int n, int maxlib, int *libi, int *libj)
Find the liberties of the string at(m, n)
, which must not be empty. The locations of up to maxlib liberties are written into(libi[], libj[])
. The full number of liberties is returned. If you want the locations of all liberties, whatever their number, you should passMAXLIBS
as the value for maxlib and allocate space forlibi[], libj[]
accordingly.
int countlib(int m, int n)
Count the number of liberties of the string at (m,n)
, which
must not be empty.
int approxlib(int m, int n, int maxlib, int *libi, int *libj)
Find the liberties a stone of the given color would get if played at(m, n)
, ignoring possible captures of opponent stones.(m, n)
must be empty. Iflibi!=NULL
, the locations of up to maxlib liberties are written into(libi[], libj[])
. The counting of liberties may or may not be halted when maxlib is reached. The number of liberties found is returned. If you want the number or the locations of all liberties, however many they are, you should passMAXLIBS
as the value for maxlib and allocate space forlibi[], libj[]
accordingly.
int chainlinks(int m, int n, int adji[MAXCHAIN], int adjj[MAXCHAIN])
:
Returns (inadji[]
,adjj[]
arrays) the chain (strings) surrounding the string at(m, n)
. The chain is defined as the set of strings in immediate connection to the(m, n)
string. Return value is the number of strings in the chain.
void chainlinks2(int m, int n, int adji[MAXCHAIN], int adjj[MAXCHAIN], int lib)
Returns (inadji[]
,adjj[]
arrays) the strings surrounding the string at(m, n)
, which have exactlylib
liberties.
void incremental_order_moves(int mi, int mj, int color,
int si, int sj,
int *number_edges, int *number_same_string,
int *number_own, int *number_opponent,
int *captured_stones, int *threatened_stones,
int *saved_stones, int *number_open)
Help collect the data needed byorder_moves()
inreading.c
. It's the caller's responsibility to initialize the result parameters.
Hashing of go positions in a hash table (sometimes also called a
transposition table) is implemented in libboard
, in hash.c
and cache.c
to be exact.
To use the hash function, you must include hash.h
and to use the
entire hash table, you must include cache.h
in your program. The
details are described in Hashing.
GNU Go 3.0 has a move generation scheme that is substantially different from earlier versions. In particular, it is different from the method of move generation in GNU Go 2.6.
In the old scheme, various move generators suggested different moves with attached values. The highest such value then decided the move. There were two important drawbacks with this scheme:
The basic idea of the new move generation scheme is that the various move generators suggest reasons for moves, e.g. that a move captures something or connects two strings, and so on. When all reasons for the different moves have been found, the valuation starts. The primary advantages are
The engine of GNU Go takes a position and a color to move and generates the (supposedly) optimal move. This is done by the function genmove() in engine/genmove.c.
The move generation is done in three steps:
This is somewhat simplified. In reality there is some overlap between the steps.
First we have to collect as much information as possible about the current position. Such information could be life and death of the groups, moyo status, connection of groups and so on. Information gathering are performed by the following functions, called in this order:
make_worms
Collect information about all connected sets of stones
(strings) and cavities. This information is stored in
the worm[][]
array.
make_dragons
Collect information about connected strings, which are called dragons. Important information here is number of eyes, life status, and connectedness between strings. The information is stored mainly in the arraydragon[][]
but also indragon2[][]
.
See Examining the Position, for a more exact itinerary of the information-gathering portion of the move-generation proces.
See Worms and Dragons, for more detailed documentation about
make_worms
and make_dragons
.
Each move generator suggests a number of moves. It justifies each move suggestion with one or move move reasons. These move reasons are collected at each intersection where the moves are suggested for later valuation. The different kinds of move reasons considered by GNU Go are:
ATTACK_MOVE
DEFEND_MOVE
ATTACK_THREAT_MOVE
DEFEND_THREAT_MOVE
NON_ATTACK_MOVE
NON_DEFEND_MOVE
ATTACK_EITHER_MOVE
DEFEND_BOTH_MOVE
CONNECT_MOVE
CUT_MOVE
ANTISUJI_MOVE
SEMEAI_MOVE
SEMEAI_THREAT
EXPAND_TERRITORY_MOVE
BLOCK_TERRITORY_MOVE
EXPAND_MOYO_MOVE
VITAL_EYE_MOVE
STRATEGIC_ATTACK_MOVE
STRATEGIC_DEFEND_MOVE
OWL_ATTACK_MOVE
OWL_DEFEND_MOVE
OWL_ATTACK_THREAT
OWL_DEFEND_THREAT
OWL_PREVENT_THREAT
UNCERTAIN_OWL_ATTACK
UNCERTAIN_OWL_DEFENSE
MY_ATARI_ATARI_MOVE
YOUR_ATARI_ATARI_MOVE
NOTE: Some of these are reasons for not playing a move.
More detailed discussion of these move reasons will be found in the next section.
A move which tactically captures a worm is called an attack move and a move which saves a worm from being tactically captured is called a defense move. It is understood that a defense move can only exist if the worm can be captured, and that a worm without defense only is attacked by moves that decrease the liberty count or perform necessary backfilling.
It is important that all moves which attack or defend a certain string are found, so that the move generation can make an informed choice about how to perform a capture, or find moves which capture and/or defend several worms.
Attacking and defending moves are first found in make_worms
while it
evaluates the tactical status of all worms, although this step only
gives one attack and defense (if any) move per worm. Immediately
after, still in make_worms
, all liberties of the attacked worms are
tested for additional attack and defense moves. More indirect moves
are found by find_attack_patterns
and find_defense_patterns
,
which match the A (attack) and D (defense) class patterns in
patterns/attack.db
and patterns/defense.db
As a final step, all
moves which fill some purpose at all are tested whether they additionally
attacks or defends some worm. (Only unstable worms are analyzed.)
A threat to attack a worm, but where the worm can be defended is used as a secondary move reason. This move reason can enhance the value of a move so that it becomes sente. A threatening move without any other justification can also be used as a ko threat. The same is true for a move that threatens defense of a worm, but where the worm can still be captured if the attacker doesn't tenuki.
Threats found by the owl code are called owl threats and they have their own owl reasons.
The tactical reading may come up with ineffective attacks or defenses occasionally. When these can be detected by patterns, it's possible to cancel the attack and/or defense potential of the moves by using these move reasons. This can only be done by action lines in the patterns.
Sometimes a move attacks at least one of a number of worms or simultaneously defends all of several worms. These moves are noted by their own move reasons.
Moves which connect two distinct dragons are called connecting moves
.
Moves which prevent such connections are called cutting moves. Cutting
and connecting moves are primarily found by pattern matching, the C
and B
class patterns.
A second source of cutting and connecting moves comes from the attack and defense of cutting stones. A move which attacks a worm automatically counts as a connecting move if there are multiple dragons adjacent to the attacked worm. Similarly a defending move counts as a cutting move. The action taken when a pattern of this type is found is to induce a connect or cut move reason.
When a cut or connect move reason is registered, the involved dragons are of course stored. Thus the same move may cut and/or connect several pairs of dragons.
A move which is necessary to win a capturing race is called a semeai move. These are similar to attacking moves, except that they involve the simultaneous attack of one worm and the defense of another. As for attack and defense moves, it's important that all moves which win a semeai are found, so an informed choice can be made between them.
Semeai move reasons should be set by the semeai module. However this has not been implemented yet. One might also wish to list moves which increase the lead in a semeai race (removes ko threats) for use as secondary move reasons. Analogously if we are behind in the race.
A move which makes a difference in the number of eyes produced from an eye space is called an eye move. It's not necessary that the eye is critical for the life and death of the dragon in question, although it will be valued substantially higher if this is the case. As usual it's important to find all moves that change the eye count.
(This is part of what eye_finder was doing. Currently it only finds one vital point for each unstable eye space.)
Moves which are locally inferior or for some other reason must not be played are called antisuji moves. These moves are generated by pattern matching. Care must be taken with this move reason as the move under no circumstances will be played.
Any move that increases territory gets a move reason. These are
the block territory and expand territory move reasons. Such move
reasons are added by the b
and e
patterns in
patterns/patterns.db
. Similarly the E
patterns attempt to
generate or mitigate an moyo, which is a region of influence not yet secure
territory, yet valuable. Such a pattern sets the "expand moyo" move
reason.
Just as the tactical reading code tries to determine when a worm
can be attacked or defended, the owl code tries to determine
when a dragon can get two eyes and live. The function owl_reasons()
generates the corresponding move reasons.
The owl attack and owl defense move reasons are self explanatory.
The owl attack threat reason is generated if owl attack on an
opponent's dragon fails but the owl code determines that the
dragon can be killed with two consecutive moves. The killing
moves are stored in (dragon[ai][aj].owl_attacki_i,
dragon[ai][aj].owl_attacki_j)
and
(dragon[ai][aj].owl_second_attacki_i,
dragon[ai][aj].owl_second_attacki_j)
.
Similarly if a friendly dragon is dead but two moves can revive it, an owl defense threat move reason is generated.
The prevent threat reasons are similar but with the colors reversed: if the opponent has an attack threat move then a move which removes the threat gets a prevent threat move reason.
The owl uncertain move reasons are generated when the owl code runs out of nodes. In order to prevent the owl code from running too long, a cap is put on the number of nodes one owl read can generate. If this is exceeded, the reading is cut short and the result is cached as usual, but marked uncertain. In this case an owl uncertain move reason may be generated. For example, if the owl code finds the dragon alive but is unsure, a move to defend may still be generated.
The function atari_atari
tries to find a sequence of ataris
culminating in an unexpected change of status of any opponent string,
from ALIVE to CRITICAL, or from CRITICAL to DEAD. Once such a sequence
of ataris is found, it tries to shorten it by rejecting irrelevant
moves.
Moves are valued with respect to five different criteria. These are
All of these are floats and should be measured in terms of actual points.
Territorial value is the amount of secure territory generated (or saved) by the move. Attack and defense moves have territorial values given by twice the number of stones in the worm plus adjacent empty space. This value is in practice approximated from the "effective size" measure.
Influence value is an estimation of the move's effect on the size of potential territory and possibly "area". This is currently implemented by using delta_moyo_simple(). This can probably be improved quite a bit. If the move captures some stones, this fact should be taken into account when computing moyo/area.
Strategical value is a measure of the effect the move has on the safety of all groups on the board. Typically cutting and connecting moves have their main value here. Also edge extensions, enclosing moves and moves towards the center have high strategical value. The strategical value should be the sum of a fraction of the territorial value of the involved dragons. The fraction is determined by the change in safety of the dragon.
Shape value is a purely local shape analysis, which primarily is intended to choose between moves having the same set of reasons. An important role of this measure is to offset mistakes made by the estimation of territorial and influence values. In open positions it's often worth sacrificing a few points of (apparent) immediate profit to make good shape. Shape value is implemented by pattern matching, the Shape patterns.
Secondary value is given for move reasons which by themselves are not sufficient to play the move. One example is to reduce the number of eyes for a dragon that has several or to attack a defenseless worm.
When all these values have been computed, they are summed, possibly weighted (secondary value should definitely have a small weight), into a final move value. This value is used to decide the move.
The algorithm for computing territorial value is in the function
estimate_territorial_value
. As the name suggests, it seeks
to estimate the amount the move adds to secure territory.
This function examines every reason for the move and takes into account the safety of different dragons. For example if the reason for the move is that it attacks and kills a worm, no value is assigned if the worm is already DEAD. If the worm is not DEAD the value of the move is twice the effective size of the worm.
In addition to such additions to territory, if the move is
found to be a block or expanding move, the function
influence_delta_territory
is consulted to find areas
where after the move the influence function becomes so strong
that these are counted as secure territory, or where the
influence function is sufficiently weakened that these are
removed from the secure territory of the opponent
(see Influential Functions).
The function estimate_influence_value
attempts to assign
a value to the influence a move. The functions
influence_delta_strict_moyo
influence_delta_strict_area
are called to find areas
where after the move the influence function becomes strong
enough that these are counted as friendly moyo or area, or
which are taken away from the opponent's moyo or area
(see Influential Functions).
Strategical defense or attack reasons are assigned to any move
which matches a pattern of type a
or d
. These are
moves which in some (often intangible) way tend to help
strengthen or weaken a dragon. Of course strengthening a
dragon which is already alive should not be given much value,
but when the move reason is generated it is not necessary
to check its status or safety. This is done later, during
the valuation phase.
In the value field of a pattern (see Pattern Values) one may specify a shape value.
This is used to compute the shape factor, which multiplies the score of a move. We take the largest positive contribution to shape and add 1 for each additional positive contribution found. Then we take the largest negative contribution to shape, and add 1 for each additional negative contribution. The resulting number is raised to the power 1.05 to obtain the shape factor.
The rationale behind this complicated scheme is that every shape point is very significant. If two shape contributions with values (say) 5 and 3 are found, the second contribution should be devalued to 1. Otherwise the engine is too difficult to tune since finding multiple contributions to shape can cause significant overvaluing of a move.
A pattern may assign a minimum (and sometimes also a maximum)
value. For example the Joseki patterns have values which are
prescribed in this way, or ones with a value
field.
One prefers not to use this approach but in practice it is
sometimes needed.
Secondary move reasons are weighed very slightly. Such a move can tip the scales if all other factors are equal.
Followup value refers to value which may acrue if we get two
moves in a row in a local area. It is assigned by the function
add_followup_value
, for example through the
followup_value
autohelper macro.
Attack and defense threats, including owl threats are usually given a small amount of weight, as is followup value.
If the largest move on the board is a ko which we cannot legally take, then such a move becomes attractive as a ko threat and the followup value or the value of the threat are taken in full.
The following functions are defined in move_reasons.c
.
void clear_move_reasons(void)
Initialize move reason data structures.
void add_lunch(int ai, int aj, int bi, int bj)
See if a lunch is already in the list of lunches, otherwise add a new entry. A lunch is in this context a pair of eater (a dragon) and food (a worm).
void remove_lunch(int ai, int aj, int bi, int bj)
Remove a lunch from the list of lunches.
void add_defense_move(int ti, int tj, int ai, int aj)
Add to the reasons for the move at (ti, tj) that it defends the worm at (ai, aj).
int defense_move_known(int ti, int tj, int ai, int aj)
Query whether a defense move is already known. Add to the reasons for the move at (ti, tj) that it attacks the worm at (ai, aj).
int attack_move_known(int ti, int tj, int ai, int aj)
Query whether an attack move is already known.
void remove_defense_move(int ti, int tj, int ai, int aj)
Remove from the reasons for the move at (ti, tj) that it defends the worm at (ai, aj). We do this by adding a NON_DEFEND move reason and wait until later to actually remove it. Otherwise it may be added again. We must also check that there do exist a defense move reason for this worm. Otherwise we may end up in an infinite loop when trying to actually remove it.
void remove_attack_move(int ti, int tj, int ai, int aj)
Remove from the reasons for the move at (ti, tj) that it attacks the worm at (ai, aj). We do this by adding a NON_ATTACK move reason and wait until later to actually remove it. Otherwise it may be added again.
void add_connection_move(int ti, int tj, int ai, int aj, int bi, int bj)
Add to the reasons for the move at (ti, tj) that it connects the dragons at (ai, aj) and (bi, bj). Require that the dragons are distinct.
void add_cut_move(int ti, int tj, int ai, int aj, int bi, int bj)
Add to the reasons for the move at (ti, tj) that it cuts the dragons at (ai, aj) and (bi, bj). Require that the dragons are distinct.
void add_antisuji_move(int ti, int tj)
Add to the reasons for the move at (ti, tj) that it is an anti-suji. This means that it's a locally inferior move or for some other reason must not be played.
void add_semeai_move(int ti, int tj, int ai, int aj, int bi, int bj)
Add to the reasons for the move at (ti, tj) that it wins a semeai between my worm at (ai, aj) and your worm at (bi, bj).
void add_vital_eye_move(int ti, int tj, int ai, int aj, int color)
Add to the reasons for the move at (ti, tj) that it's the vital point for the eye space at (ai, aj) of color color.
void add_attack_either_move(int ti, int tj, int ai, int aj, int bi, int bj)
Add to the reasons for the move at (ti, tj) that it attacks either (ai, aj) or (bi, bj) (e.g. a double atari). This move reason is only used for double attacks on opponent stones. Before accepting the move reason, check that the worms are distinct and that neither is undefendable.
void add_defend_both_move(int ti, int tj, int ai, int aj, int bi, int bj)
Add to the reasons for the move at (ti, tj) that it defends both (ai, aj) and (bi, bj) (e.g. from a double atari). This move reason is only used for defense of own stones.
void add_block_territory_move(int ti, int tj)
Add to the reasons for the move at (ti, tj) that it secures territory by blocking.
void add_expand_territory_move(int ti, int tj)
Add to the reasons for the move at (ti, tj) that it expands territory.
void add_expand_moyo_move(int ti, int tj)
Add to the reasons for the move at (ti, tj) that it expands moyo.
void add_shape_value(int ti, int tj, float value)
Increase or decrease the shape value for the move at (ti, tj).
void add_strategical_attack_move(int ti, int tj, int ai, int aj)
Add to the reasons for the move at (ti, tj) that it attacks the dragon (ai, aj) on a strategical level.
void add_strategical_defense_move(int ti, int tj, int ai, int aj)
Add to the reasons for the move at (ti, tj) that it defends the dragon (ai, aj) on a strategical level.
void add_followup_value(int ti, int tj, float value)
Add value of followup moves.
void set_minimum_move_value(int ti, int tj, float value)
Set a minimum allowed value for the move.
void set_maximum_move_value(int ti, int tj, float value)
Set a maximum allowed value for the move.
void set_minimum_territorial_value(int ti, int tj, float value)
Set a minimum allowed territorial value for the move.
void set_maximum_territorial_value(int ti, int tj, float value)
Set a maximum allowed territorial value for the move.
int review_move_reasons(int *i, int *j, float *val, int color)
Review the move reasons to find which (if any) move we want to play.
The following functions in move_reasons.c
are declared
static. Their scope is limited to that file.
static int find_worm(int ai, int aj)
Find the index of a worm in the list of worms. If necessary, add a new entry. (ai, aj) must point to the origin of the worm.
static int find_dragon(int ai, int aj)
Find the index of a dragon in the list of dragons. If necessary, add a new entry. (ai, aj) must point to the origin of the dragon.
static int find_connection(int dragon1, int dragon2)
Find the index of a connection in the list of connections. If necessary, add a new entry.
static int find_semeai(int myworm, int yourworm)
Find the index of a semeai in the list of semeais. If necessary, add a new entry.
static int find_worm_pair(int worm1, int worm2)
Find the index of an unordered pair of worms in the list of worm pairs. If necessary, add a new entry.
static int find_eye(int i, int j, int color)
Find the index of an eye space in the list of eye spaces. If necessary, add a new entry.
static int find_reason(int type, int what)
Find a reason in the list of reasons. If necessary, add a new entry.
static void add_move_reason(int ti, int tj, int type, int what)
Add a move reason for (ti, tj) if it's not already there or the table is full.
static void remove_move_reason(int ti, int tj, int type, int what)
Remove a move reason for (ti, tj). Ignore silently if the reason wasn't there.
static int move_reason_known(int ti, int tj, int type, int what)
Check whether a move reason already is recorded for a move.
static void find_more_attack_and_defense_moves(int color)
Test all moves that defends, attacks, connects or cuts to see if they also attack or defend some other worm.
static void remove_opponent_attack_and_defense_moves(int color)
Remove attacks on own stones and defense of opponent stones, i.e. moves which are only relevant for the opponent. It might seem useful to take these into account (proverb "my enemy's vital point is my vital point") but now it seems they only lead to trouble. It's easiest just to remove them altogether.
static void do_remove_false_attack_and_defense_moves(void)
Remove attacks and defenses that have earlier been marked as NON_ATTACK or NON_DEFEND respectively, because they actually don't work.
static int strategically_sound_defense(int ai, int aj, int ti, int tj)
It's often bad to run away with a worm that is in a strategically weak position. This function gives heuristics for determining whether a move at (ti, tj) to defend the worm (ai, aj) is strategically sound. These heuristics need improvement. The biggest weakness is that they sometimes fail to detect when we're running away towards open ground. It would help much to have a reliable escape route mechanism.
static void induce_secondary_move_reasons(int color)
Any move that captures or defends a worm also connects or cuts the surrounding dragons. Find these secondary move reasons.
- There is a certain amount of optimizations that could be done here.
- Even when we defend a worm, it's possible that the opponent still can secure a connection, e.g. underneath a string with few liberties. Thus a defense move isn't necessarily a cut move.
- Connections are transitive. If a move connects A with B and B with C, we should infer that it connects A with C as well.
static float effective_dragon_size(int ai, int aj)
Measure the "effective" size of a dragon. This measure is a reasonable approximation of how much area a dragon cover, including some amount of surrounding empty spaces.
static float dragon_safety(int ai, int aj, int ignore_dead_dragons)
An attempt to estimate the safety of a dragon. This should be possible to improve considerably. The resulting value is interpreted so that 1.0 means a fully safe dragon while 0.0 is an almost dead dragon.
static float connection_value2(int ai, int aj, int bi, int bj, int ti, int tj)
Strategical value of connecting (or cutting) the dragon at (ai, aj) to the dragon at (bi, bj). This function is assymetric.
static void estimate_territorial_value(int m, int n, int color)
Estimate the direct territorial value of a move at (m,n).
static void estimate_influence_value(int m, int n, int color)
Estimate the influence value of a move at (m,n).
static void estimate_strategical_value(int m, int n, int color)
Estimate the strategical value of a move at (m,n).
static int is_antisuji_move(int m, int n)
Look through the move reasons to see whether (m, n) is an antisuji move.
static float value_move_reasons(int m, int n, int color)
Combine the reasons for a move at (m, n) into an old style value. These heuristics are now somewhat less ad hoc but probably still need a lot of improvement.
static void value_moves(int color)
Loop over all possible moves and value the move reasons for each.
Endgame moves are generated just like any other move by GNU Go. In fact,
the concept of endgame does not exist explicitly, but if the largest
move initially found is worth 6 points or less, an extra set of patterns
in endgame.db
is matched and the move valuation is redone.
Before considering its move, GNU Go collects some data in several
arrays. Two of these arrays, called worm
and dragon
, are
discussed in this document. Others are discussed in See Eyes.
This information is intended to help evaluate the connectedness, eye shape, escape potential and life status of each group.
Later routines called by genmove()
will then have access to this
information. This document attempts to explain the philosophy and
algorithms of this preliminary analysis, which is carried out by the
two routines make_worm()
and make_dragon()
in
dragon.c
.
A worm is a maximal set of vertices on the board which are connected
along the horizontal and vertical lines, and are of the same color,
which can be BLACK
, WHITE
or EMPTY
. The term
EMPTY
applied to a worm means that the worm consists of empty
(unoccupied) vertices. It does not mean that that the worm is the
empty set. A string is a nonempty worm. An empty worm is called a
cavity. If a subset of vertices is contained in a worm, there is a
unique worm containing it; this is its worm closure.
A dragon is a union of strings of the same color which will be treated as a unit. The dragons are generated anew at each move. If two strings are in the dragon, it is the computer's working hypothesis that they will live or die together and are effectively connected.
The purpose of the dragon code is to allow the computer to formulate meaningful statements about life and death. To give one example, consider the following situation:
OOOOO OOXXXOO OX...XO OXXXXXO OOOOO
The X's here should be considered a single group with one three-space eye, but they consist of two separate strings. Thus we must amalgamate these two strings into a single dragon. Then the assertion makes sense, that playing at the center will kill or save the dragon, and is a vital point for both players. It would be difficult to formulate this statement if the X's are not perceived as a unit.
The present implementation of the dragon code involves simplifying assumptions which can be refined in later implementations.
The array struct worm_data worm[MAX_BOARD][MAX_BOARD]
collects information about the
worms. We will give definitions of the various fields. Each field has
constant value at each vertex of the worm. We will define each field.
struct worm_data { int color; int size; float effective_size; int origini; int originj; int liberties; int liberties2; int liberties3; int liberties4; int attacki; int attackj; int attack_code; int defendi; int defendj; int defend_code; int lunchi; int lunchj; int cutstone; int cutstone2; int genus; int value; int ko; int inessential; int invincible; int unconditional_status; };
color
If the worm isBLACK
orWHITE
, that is its color. Cavities (empty worms) have an additional attribute which we call bordercolor. This will be one ofBLACK_BORDER,
WHITE_BORDER
orGRAY_BORDER
. Specifically, if all the worms adjacent to a given empty worm have the same color (black or white) then we define that to be the bordercolor. Otherwise the bordercolor is gray.Rather than define a new field, we keep this data in the field color. Thus for every worm, the color field will have one of the following values:
BLACK
,WHITE
,GRAY_BORDER
,BLACK_BORDER
orWHITE_BORDER
. The last three categories are empty worms classified by bordercolor.
size
This field contains the cardinality of the worm.
effective_size
This is the number of stones in a worm plus the number of empty intersections that are at least as close to this worm as to any other worm. Intersections that are shared are counted with equal fractional values for each worm. This measures the direct territorial value of capturing a worm. effective_size is a floating point number. Only intersections at a distance of 4 or less are counted.
(origini, originj)
Each worm has a distinguished member, called its origin. Its coordinates are(origini, originj)
. The purpose of this field is to make it easy to determine when two vertices lie in the same worm: we compare their origin. Also if we wish to perform some test once for each worm, we simply perform it at the origin and ignore the other vertices. The origin is characterized by the test:(worm[m][n].origini == m) && (worm[m][n].originj == n).
liberties
For a nonempty worm the field liberties is the number of liberties of the string. This is supplemented byLIBERTIES2
,LIBERTIES3
andLIBERTIES4
, which are the number of second order, third order, and fourth order liberties, respectively. The definition of liberties of order >1 is adapted to the problem of detecting the shape of the surrounding cavity. In particular we want to be able to see if a group is loosely surrounded. a liberty of order n is an empty vertex which may be connected to the string by placing n stones of the same color on the board, but no fewer. The path of connection may pass through an intervening group of the same color. The stones placed at distance >1 may not touch a group of the opposite color. Connections through ko are not permitted. Thus in the following configuration:.XX... We label the .XX.4. XO.... liberties of XO1234 XO.... order < 5 of XO1234 ...... the O group: .12.4. .X.X.. .X.X..The convention that liberties of order >1 may not touch a group of the opposite color means that knight's moves and one space jumps are perceived as impenetrable barriers. This is useful in determining when the string is becoming surrounded.The path may also not pass through a liberty at distance 1 if that liberty is flanked by two stones of the opposing color. This reflects the fact that the O stone is blocked from expansion to the left by the two X stones in the following situation:
X. .O X.We say that n is the distance of the liberty of order n from the dragon.
(attacki, attackj)
:
If it is determined that the string may be easily captured,(attacki, attackj)
points to an attacking move. This is only used for strings with <5 liberties. If no attacking move is found, thenattack_code == 0
.
attack_code
1 if the worm can be captured unconditionally, 2 or 3 if it can be captured with ko. If it can be captured provided the attacker is willing to ignore any ko threat, then theattack_code == 2
. If it can be captured provided the attacker can come up with a sufficiently large ko threat, then theattack_code == 3
.
lunch
Iflunchi != -1
then(lunchi, lunchj)
points to a boundary worm which can be easily captured. (It does not matter whether or not the string can be defended.)
defend
:
If there is an attack on the string (stored in theattack
field defined above), and there is a move which defends the string, this move is stored in(defendi, defendj)
. Otherwisedefend_code == 0
.
defend_code
1 if the worm can be defended unconditionally, 2 or 3 if it can be defended with ko. If it can be defended provided the defender is willing to ignore any ko threat, then thedefend_code == 2
. If it can be captured provided the defender can come up with a sufficiently large ko threat, then thedefend_code == 3
. If there is no attack,defend_code
is 0.
We have two distinct notions of cutting stone, which we keep track
of in the separate fields worm.cutstone
and worm.cutstone2
.
We maintain both fields because the historically older cutstone
field is needed to deal with the fact that e.g. in the position
OXX.O .OOXO OXX.O
the X stones are amalgamated into one dragon because neither cut works as long as the two O stones are in atari. Therefore we add one to the cutstone field for each potential cutting point, indicating that these O stones are indeed worth rescuing.
For the time being we use both concepts in parallel. It's possible we also old concept for correct handling of lunches.
cutstone
:
This field is equal to 2 for cutting stones, 1 for potential cutting stones. Otherwise it is zero. Definitions for this field: a cutting stone is one adjacent to two enemy strings, which do not have a liberty in common. The most common type of cutting string is in this situation:XO OXA potential cutting stone is adjacent to two enemy strings which do share a liberty. For example, X in:
XO O.For cutting strings we set
worm[m][n].cutstone=2
. For potential cutting strings we setworm[m][n].cutstone=1
.
cutstone2
:
Cutting points are identified by the patterns in the connections database. Proper cuts are handled by the fact that attacking and defending moves also count as moves cutting or connecting the surrounding dragons. The cutstone2 field is set during find_cuts(), called from make_domains().The
cutstone2
field is needed to deal with the fact that e.g. in the positionOXX.O .OOXO OXX.Othe X stones are amalgamated into one dragon because neither cut works as long as the two O stones are in atari. Therefore we add one to the cutstone field for each potential cutting point, indicating that these O stones are indeed worth rescuing.
For the time being we use both concepts in parallel, with the new concept stored in
cutstone2
. It's possible that we have to keep the old concept for correct handling of lunches.
genus
:
There are two separate notions of genus for worms and dragons. The dragon notion is more important, sodragon[m][n].genus
is a far more useful field thanworm[m][n].genus
. Both fields are intended as approximations to the number of eyes. The genus of a string is the number of connected components of its complement, minus one. It is an approximation to the number of eyes of the string.
ko
:
For every ko, the flagko
is set to 1 at the ko stone which is in atari, and also at the ko cavity adjacent to it. Thus in this situation:XO X.XO XOthe flag
ko
is set to 1 at the rightmost X stone, and also at the cavity to its left.
inessential
:
An inessential string is one which meets a criterion designed to guarantee that it has no life potential unless a particular surrounding string of the opposite color can be killed. More precisely an inessential string is a string S of genus zero, not adjacent to any opponent string which can be easily captured, and which has no edge liberties or second order liberties, and which satisfies the following further property: If the string is removed from the board, then the empty worm E which is the worm closure of the set of vertices which it occupied has bordercolor the opposite of the removed string. The empty worm E (empty, that is, as a worm of the board modified by removal of S) consists of the union of support of S together with certain other empty worms which we call the boundary components of S.The inessential strings are used in the amalgamation of cavities in
make_dragon()
.
invincible
:
An invincible worm is one which GNU Go thinks
cannot be captured. Invincible worms are computed by the
function unconditional_life()
which tries to
find those worms of the given color that can never be captured,
even if the opponent is allowed an arbitrary number of consecutive
moves.
Unconditional status is also set by the functionunconditional_life
. This is set ALIVE for stones which are invincible. Stones which can not be turned invincible even if the defender is allowed an arbitrary number of consecutive moves are given an unconditional status of DEAD. Empty points where the opponent cannot form an invincible worm are called unconditional territory. The unconditional status is set to WHITE_BORDER or BLACK_BORDER depending on who owns the territory. Finally, if a stone can be captured but is adjacent to unconditional territory of its own color, it is also given the unconditional status ALIVE. In all other cases the unconditional status is UNKNOWN.To make sense of these definitions it is important to notice that any stone which is alive in the ordinary sense (even if only in seki) can be transformed into an invincible group by some number of consecutive moves. Well, this is not entirely true because there is a rare class of seki groups not satisfying this condition. Exactly which these are is left as an exercise for the reader. Currently
unconditional_life
, which strictly follows the definitions above, calls such seki groups unconditionally dead, which of course is a misfeature. It is possible to avoid this problem by making the algorithm slightly more complex, but this is left for a later revision.
The function makeworms()
will generate data for all worms. For
empty worms, the following fields are significant: color
,
size
, origini
and originj
. The liberty
,
attack
, defend
, cutstone
, genus
and
inessential
fields have significance only for nonempty worms.
A dragon, we have said, is a group of stones which are treated as a unit. It is a working hypothesis that these stones will live or die together. Thus the program will not expect to disconnect an opponent's strings if they have been amalgamated into a single dragon.
The function make_dragons()
will amalgamate worms into dragons by
maintaining separate arrays worm[]
and dragon[]
containing
similar data. Each dragon is a union of worms. Just as the data maintained in
worm[][]
is constant on each worm, the data in
dragon[][]
is constant on each dragon.
Amalgamation of two worms means means in practice replacing the origin of one worm by the origin of the other. Amalgamation takes place in two stages: first, the amalgamation of empty worms (cavities) into empty dragons (caves); then, the amalgamation of colored worms into dragons.
As we have already defined it, a cavity is an empty worm. A cave is an empty dragon.
Under certain circumstances we want to amalgamate two or more cavities into a single cave. This is done before we amalgamate strings. An example where we wish to amalgamate two empty strings is the following:
OOOOO OOXXXOO OXaObXO OOXXXOO OOOOO
The two empty worms at a and b are to be amalgamated.
We have already defined a string to be inessential if it meets a criterion designed to guarantee that it has no life potential unless a particular surrounding string of the opposite color can be killed. An inessential string is a string S of genus zero which is not a cutting string or potential cutting string, and which has no edge liberties or second order liberties (the last condition should be relaxed), and which satisfies the following further property: If the string is removed from the board, then the empty worm E which is the worm closure of the set of vertices which it occupied has bordercolor the opposite of the removed string.
Thus in the previous example, after removing the inessential string at the center the worm closure of the center vertex consists of an empty worm of size 3 including a and b. The latter are the boundary components.
The last condition in the definition of inessential worms excludes examples such as this:
OOOO OXXOO OXX.XO OX.XXO OOXXO OOO
Neither of the two X strings should be considered inessential (together they form a live group!) and indeed after removing one of them the resulting space has gray bordercolor, so by this definition these worms are not inessential.
Some strings which should by rights be considered inessential will be missed by this criterion.
The algorithm for amalgamation of empty worms consists of amalgamating the boundary components of any inessential worm. The resulting dragon has bordercolor the opposite of the removed string.
Any dragon consisting of a single cavity has bordercolor equal to that of the cavity.
Amalgamation of nonempty worms in GNU Go 3.0 proceeds as follows. First we amalgamate all boundary components of an eyeshape. Thus in the following example:
.OOOO. The four X strings are amalgamated into a OOXXO. single dragon because they are the boundary OX..XO components of a blackbordered cave. The OX..XO cave could contain an inessential string OOXXO. with no effect on this amalgamation. XXX...
The code for this type of amalgamation is in the routine
dragon_eye()
, discussed further in EYES.
Next, we amalgamate strings which seem uncuttable. We amalgamate dragons which either share two or more common liberties, or share one liberty into the which the opponent cannot play without being captured. (ignores ko rule).
X. X.X XXXX.XXX X.O .X X.X X......X X.X XXXXXX.X OXX
A database of connection patterns may be found in patterns/conn.db
.
The fields black_eye.cut
and white_eye.cut
are set where the
opponent can cut, and this is done by the B (break) class patterns in
conn.db
. There are two important uses for this field, which can be
accessed by the autohelper functions xcut()
and ocut()
. The
first use is to stop amalgamation in positions like
..X.. OO*OO X.O.X ..O..
where X can play at * to cut off either branch. What happens here is that first connection pattern CB1 finds the double cut and marks * as a cutting point. Later the C (connection) class patterns in conn.db are searched to find secure connections over which to amalgamate dragons. Normally a diagonal connection would be deemed secure and amalgamated by connection pattern CC101, but there is a constraint requiring that neither of the empty intersections is a cutting point.
A weakness with this scheme is that X can only cut one connection, not
both, so we should be allowed to amalgamate over one of the connections.
This is performed by connection pattern CC401, which with the help of
amalgamate_most_valuable_helper()
decides which connection to
prefer.
The other use is to simplify making alternative connection patterns to
the solid connection. Positions where the diag_miai helper thinks a
connection is necessary are marked as cutting points by connection
pattern 12. Thus we can write a connection pattern like CC6
:
?xxx? straight extension to connect XOO*? O...? :8,C,NULL ?xxx? XOOb? Oa..? ;xcut(a) && odefend_against(b,a)
where we verify that a move at *
would stop the enemy from safely
playing at the cutting point, thus defending against the cut.
A half eye is a place where, if the defender plays first, an eye will materialize, but where if the attacker plays first, no eye will materialize. A false eye is a vertex which is surrounded by a dragon yet is not an eye. Here is a half eye:
XXXXX OO..X O.O.X OOXXX
Here is a false eye:
XXXXX XOO.X O.O.X OOXXX
The "topological" algorithm for determining half and false eyes is described elsewhere (see Eye Topology).
The half eye data is collected in the dragon array. Before this is done,
however, an auxiliary array called half_eye_data is filled with
information. The field type
is 0, or else HALF_EYE
or
FALSE_EYE
depending on which type is found; and
(ki, kj)
points to a move to kill the half eye.
struct half_eye_data half_eye[MAX_BOARD][MAX_BOARD]; struct half_eye_data { int type; /* HALF_EYE or FALSE_EYE; */ int num_attacks; /* number of attacking points */ int num_defends; /* number of defending points */ int ai[4]; /* (ai, aj) attacks a topological halfeye */ int aj[4]; int di[4]; /* (di, dj) defends a topological halfeye */ int dj[4]; };
The array struct half_eye_data half_eye[MAX_BOARD][MAX_BOARD]
contains information about half and false eyes. If the type is
HALF_EYE
then up to four moves are recorded which can
either attack or defend the eye. In rare cases the attack points
could be different from the defense points.
The array struct dragon_data dragon[MAX_BOARD][MAX_BOARD]
collects information about the dragons. We will give definitions of the
various fields. Each field has constant value at each vertex of the
dragon.
struct dragon_data { int color; int id; int origini; int originj; int borderi; int borderj; int size; float effective_size; int heyes; int heyei; int heyej; int genus; int escape_route; int lunchi; int lunchj; int status; int owl_status; int owl_attacki; int owl_attackj; int owl_attack_certain; int owl_second_attacki; int owl_second_attackj; int owl_defendi; int owl_defendj; int owl_defend_certain; int owl_second_defendi; int owl_second_defendj; int old_safety; int matcher_status; int semeai; int semeai_margin_of_safety; };
Here are the definitions of each field.
color
:
For strings, this isBLACK
orWHITE
. For caves, it isBLACK_BORDER
,WHITE_BORDER
orGRAY_BORDER
. The meaning of these concepts is the same as for worms.
id
:
This is a pointer to the dragon's field in the dragon2
array
(see Dragon2).
(origini, originj)
The origin of the dragon is a unique particular vertex of the dragon, useful for determining when two vertices belong to the same dragon. Before amalgamation the worm origins are copied to the dragon origins. Amalgamation of two dragons amounts to changing the origin of one.
(borderi, borderj)
This field is relevant for caves. If the color of the cave isBLACK_BORDER
orWHITE_BORDER
then the surrounding worms all have the same colorBLACK
orWHITE
and these have been amalgamated into a dragon with origin(borderi, borderj)
.
size
:
This is the cardinality of the dragon.
effective_size
:
The sum of the effective sizes of the constituent worms.
Remembering that vertices equidistant between two or more worms are
counted fractionally in worm.effective_size
, this equals the
cardinality of the dragon plus the number of empty vertices which are
nearer this dragon than any other.
heyes
:
This is the number of half eyes the dragon has. A half eye is a pattern where an eye may or may not materialize, depending on who moves first.
(heyi,heyj)
:
If any half eyes are found, (heyi,heyj)
points to a move which will
create an eye.
genus
:
The genus of a nonempty dragon consists of the number of distinct adjacent caves whose bordercolor is the color of the dragon, minus the number of false eyes found. The genus is a computable approximation to the number of eyes a dragon has.
escape_route
:
This is a measure of the escape potential of the dragon. If
dragon.escape_route
is large, GNU Go believes that the
dragon can escape, so finding two eyes locally becomes less
urgent. Further documentation may be found else where
(see Escape).
(lunchi, lunchj)
Iflunchi != -1
, then(lunchi, lunchj)
points to a boundary worm which can be captured easily. In contrast with the worm version of this parameter, we exclude strings which cannot be saved.
status
:
An attempt is made to classify the dragons asALIVE
,DEAD
,CRITICAL
orUNKNOWN
. TheCRITICAL
classification means that the fate of the dragon depends on who moves first in the area. The exact definition is in the functiondragon_status()
. If the dragon is found to be surrounded, the status isDEAD
if it has less than 1.5 eyes or if the reading code determines that it can be killed,ALIVE
if it has 2 or more eyes, andCRITICAL
if it has 1.5 eyes. A lunch generally counts as a half eye in these calculations. If it has less than 2 eyes but seems possibly able to escape, the status may beUNKNOWN
.
owl_status
This is a classification similar todragon.status
, but based on the life and death reading inowl.c
. The owl code (see The Owl Code) is only run on dragons with dragon.escape_route>5 and dragon2.moyo>10 (see Dragon2). If these conditions are not met, the owl status isUNCHECKED
. Ifowl_attack()
determines that the dragon cannot be attacked, it is classified asALIVE
. Otherwise,owl_defend()
is run, and if it can be defended it is classified asCRITICAL
, and if not, asDEAD
.
(owl_attacki, owl_attackj)
If the owl code finds that the dragon can be attacked, this is the
move. This may be tenuki (i.e. (-1,-1)
) if the owl code thinks
the group is dead as it stands.
owl_attack_certain
The functionowl_attack
, which is used to set(owl_attacki, owl_attackj)
, is given an upper bound ofowl_node_limit
in the number of nodes it is allowed to generate. If this is exceeded the result is considered uncertain and this flag is set.
(owl_second_attack_i, owl_second_attack_j)
If the level is at least 8, and if a dragon is not owl attackable, the owl functionowl_threaten_attack
is asked if the dragon can be killed with two moves in a row. If two such killing moves are found, they are cached in(owl_attacki, owl_attackj)
and(owl_second_attack_i, owl_second_attack_j)
.
(owl_defendi, owl_defendj)
If the owl code finds that the dragon can be defended, this is the move.
owl_defend_certain
(owl_second_defend_i, owl_second_defend_j)
Similar to owl_attack_certain
and
(owl_second_attack_i, owl_second_attack_j)
matcher_status
This is the status used by the pattern matcher. Ifowl_status
is available (notUNCHECKED
) this is used. Otherwise, we use thestatus
field, except that we upgradeDEAD
to
UNKNOWN
.
semeai
True if the dragon is part of a semeai.
semeai_margin_of_safety
Small if the semeai is close. Somewhat unreliable.
You can get a colored ASCII display of the board in which each dragon
is assigned a different letter; and the different values of
dragon.status
values (ALIVE
, DEAD
, UNKNOWN
,
CRITICAL
) have different colors. This is very handy for debugging.
A second diagram shows the values of owl.status
. If this
is UNCHECKED
the dragon is displayed in White.
Save a game in sgf format using CGoban, or using the -o
option with
GNU Go itself.
Open an xterm
or rxvt
window. You may also use the Linux
console. Using the console, you may need to use "SHIFT-PAGE UP" to see the
first diagram. Xterm will only work if it is compiled with color support--if
you do not see the colors try rxvt
. Make the background color black
and the foreground color white.
Execute:
gnugo -l [filename] -L [movenum] -T
to get the colored display.
The color scheme: Green = ALIVE
; Yellow = UNKNOWN
;
Cyan = DEAD
and Red = CRITICAL
. Worms which have been
amalgamated into the same dragon are labelled with the same letter.
Other useful colored displays may be obtained by using instead:
The colored displays are documented elsewhere (see Colored Display).
Here are the public functions in engine/worm.c
:
void make_worms(void)
Each worm is marked with an origin, having coordinates (origini,
originj)
. This is an arbitrarily chosen element of the worm, in
practice the algorithm puts the origin at the first element when they
are given the lexicographical order, though its location is irrelevant
for applications. To see if two stones lie in the same worm, compare
their origins.
void propagate_worm(int m, int n)
propagate_worm()
takes the worm data at one stone and copies it to
the remaining members of the worm.
int examine_cavity(int m, int n, int *edge, int *size, int *vertexi, int *vertexj)
If(m, n)
is EMPTY, this function examines the cavity at(m, n)
, determines its size and returns its bordercolor, which can beBLACK_BORDER
,WHITE_BORDER
orGRAY_BORDER
. The edge parameter is set to the number of edge vertices in the cavity.(vertexi[], vertexj[])
hold the vertices of the cavity.vertexi[]
andvertexj[]
should be dimensioned to be able to hold the whole board.If
(m, n)
is nonempty, it returns the same result, imagining that the string at(m, n)
is removed. The edge parameter is set to the number of vertices where the cavity meets the edge in a point outside the removed string.
Here are the public functions in engine/dragon.c
:
void make_dragons()
This basic function finds all dragons and collects some basic information about them in the dragon array.
void show_dragons(void)
Print status info on all dragons. (Can be invoked from gdb)
void join_dragons(int ai, int aj, int bi, int bj)
Amalgamates the dragon at(ai, aj)
to the dragon at(bi, bj)
.
static int compute_dragon_status(int i, int j)
Tries to determine whether the dragon at(i, j)
isALIVE
,DEAD
, orUNKNOWN
. The algorithm is not perfect and can give incorrect answers. The dragon is judged alive if its genus is >1. It is judged dead if the genus is <2, it has no escape route, and no adjoining string can be easily captured. Otherwise it is judgedUNKNOWN
.
void compute_escape_potential(void)
Compute the escape potential for the escape2
field
(see Dragons).
In addition to dragon[][]
there is a second complementary dragon
data array dragon2[]
. In contrast to dragon[][]
, the
information in this one is not duplicated to every intersection of the
board. Instead the dragons are numbered, using the new field id in
dragon[][]
, and this number is used as index into the
dragon2[]
array. This number can of course not be assigned until
all dragon amalgamations have been finished. Neither is the
dragon2[]
array initialized until this has been done.
The first thing this array contains is a list of neighbor dragons. The intention of this information is to be able to modify the perceived safety of a dragon with respect to the strength of its neighbors. The list of neighbors should be useful for other purposes too.
For the algorithm we refer to the source code and its comments, in the
function compute_supplementary_dragon_data()
in dragon.c
.
To access the dragon[][]
array given a dragon id number or the
dragon2[]
array given a board coordinate, there are the two handy
macros DRAGON(d)
and DRAGON2(m, n)
. Also notice that the
dragon2[]
data and the id number only are valid for non-empty
dragons, i.e. not for caves.
The purpose of this Chapter is to describe the algorithm used in
GNU Go 3.0 to determine eyes. There are actually two alternative
algorithms: the graph-based algorithm in optics.c
, and
the algorithm based on reading in life.c
. The life
code is slower than the graph based algorithm, but more
accurate. You can make it the default by using the option
--life
. Otherwise, GNU Go will only call the life
code if the graph based algorithm decides that it needs
an expert opinion.
optics.c
Each connected eyespace of a dragon affords a local game which yields
a local game tree. The score of this local game is the number of eyes
it yields. Usually if the players take turns and make optimal moves,
the end scores will differ by 0 or 1. In this case, the local game may
be represented by a single number, which is an integer or half
integer. Thus if n(O)
is the score if O
moves first,
both players alternate (no passes) and make alternate moves, and
similarly n(X)
, the game can be represented by
{n(O)|n(X)}
. Thus {1|1} is an eye, {2|1} is an eye plus a
half eye, etc.
The exceptional game {2|0} can occur, though rarely. We call an eyespace yielding this local game a CHIMERA. The dragon is alive if any of the local games ends up with a score of 2 or more, so {2|1} is not different from {3|1}. Thus {3|1} is NOT a chimera.
Here is an example of a chimera:
XXXXX XOOOX XO.OOX XX..OX XXOOXX XXXXX
In order that each eyespace be assignable to a dragon,
it is necessary that all the dragons surrounding it
be amalgamated (see Amalgamation). This is the
function of dragon_eye()
.
An EYE SPACE for a black dragon is a collection of vertices adjacent to a dragon which may not yet be completely closed off, but which can potentially become eyespace. If an open eye space is sufficiently large, it will yield two eyes. Vertices at the edge of the eye space (adjacent to empty vertices outside the eye space) are called MARGINAL.
Here is an example from a game:
|. X . X X . . X O X O |X . . . . . X X O O O |O X X X X . . X O O O |O O O O X . O X O O O |. . . . O O O O X X O |X O . X X X . . X O O |X O O O O O O O X X O |. X X O . O X O . . X |X . . X . X X X X X X |O X X O X . X O O X O
Here the O
dragon which is surrounded in the center has open
eye space. In the middle of this open eye space are three
dead X
stones. This space is large enough that O cannot be
killed. We can abstract the properties of this eye shape as follows.
Marking certain vertices as follows:
|- X - X X - - X O X O |X - - - - - X X O O O |O X X X X - - X O O O |O O O O X - O X O O O |! . . . O O O O X X O |X O . X X X . ! X O O |X O O O O O O O X X O |- X X O - O X O - - X |X - - X - X X X X X X |O X X O X - X O O X O
the shape in question has the form:
!... .XXX.!
The marginal vertices are marked with an exclamation point (!
).
The captured X
stones inside the eyespace are naturally marked X
.
The precise algorithm by which the eye spaces are determined is
somewhat complex. Documentation of this algorithm is in the
comments in the source to the function make_domains()
in
src/optics.c
.
The eyespaces can be conveniently displayed using a colored
ascii diagram by running gnugo -E
.
In the abstraction, an eyespace consists of a set of vertices labelled:
! . X
Tables of many eyespaces are found in the database patterns/eyes.db
.
Each of these may be thought of as a local game. The result of this
game is listed after the eyespace in the form :max,min, where max is
the number of eyes the pattern yields if O
moves first, while
min is the number of eyes the pattern yields if X
moves
first. The player who owns the eye space is denoted O
throughout this discussion. Since three eyes are no better than two,
there is no attempt to decide whether the space yields two eyes or
three, so max never exceeds 2. Patterns with min>1 are omitted from
the table.
For example, we have:
Pattern 1 x !x*x :2,1
Here notation is as above, except that x
means X
or
EMPTY
. The result of the pattern is not different if X
has
stones at these vertices or not.
We may abstract the local game as follows. The two players O
and X
take turns moving, or either may pass.
RULE 1: O
for his move may remove any vertex marked !
or marked .
.
RULE 2: X
for his move may replace a .
by an X
.
RULE 3: X
may remove a !
. In this case, each .
adjacent to the "!" which is removed becomes a "!" . If an
"X
" adjoins the "!" which is removed, then that "X
" and any
which are connected to it are also removed. Any .
which
are adjacent to the removed X
's then become .
Thus if O
moves first he can transform the eyeshape in
the above example to:
... or !... .XXX.! .XXX.
However if X
moves he may remove the !
and the .
s
adjacent to the !
become !
themselves. Thus if X
moves first he may transform the eyeshape to:
!.. or !.. .XXX.! .XXX!
NOTE: A nuance which is that after the X:1
, O:2
exchange below, O
is threatening to capture three X stones,
hence has a half eye to the left of 2. This is subtle, and there are
other such subtleties which our abstraction will not capture. Some of
these at least can be dealt with by a refinements of the scheme, but
we will content ourselves for the time being with a simplified
|- X - X X - - X O X O |X - - - - - X X O O O |O X X X X - - X O O O |O O O O X - O X O O O |1 2 . . O O O O X X O |X O . X X X . 3 X O O |X O O O O O O O X X O |- X X O - O X O - - X |X - - X - X X X X X X |O X X O X - X O O X O
We will not attempt to characterize the terminal states of the local game (some of which could be seki) or the scoring.
Here is a local game which yields exactly one eye, no matter who moves first:
! ... ...!
Here are some variations, assuming O
moves first.
! (start position)
...
...!
... (after O
's move)
...!
...
..!
...
..
.X. (nakade)
..
Here is another variation:
! (start) ... ...! ! (afterO
's move) . . ...! ! (afterX
's move) . . ..X! . . ..X! . ! .!
It is a useful observation that the local game associated with an eyespace depends only on the underlying graph, which as a set consists of the set of vertices, in which two elements are connected by an edge if and only if they are adjacent on the Go board. For example the two eye shapes:
.. .. and ....
though distinct in shape have isomorphic graphs, and consequently
they are isomorphic as local games. This reduces the number of
eyeshapes in the database patterns/eyes.db
.
A further simplification is obtained through our treatment of
half eyes and false eyes. Such patterns are tabulated in the
database hey.h. During make_worms, which runs before the
eye space analysis, the half eye and false eye patterns are
tabulated in the array half_eye
.
A half eye is isomorphic to the pattern (!.)
. To see this,
consider the following two eye shapes:
XOOOOOO X.....O XOOOOOO and: XXOOOOO XOa...O XbOOOOO XXXXXX
These are equivalent eyeshapes, with isomorphic local games {2|1}. The first has shape:
!....
The second eyeshape has a half eye at a which is taken when O
or X
plays at b
. This is found by the topological
criterion (see Eye Topology).
ooo half eye OhO *OX
and it is recorded in the half_eye array as follows. If (i,j)
are the coordinates of the point a
, half_eye[i][j].type==HALF_EYE
and (half_eye[i][j].ki, half_eye[i][j].kj)
are the coordinates
of b
.
The graph of the eye_shape, ostensibly ....
is modified by replacing
the left .
by !
.
The patterns in patterns/eyes.db
are compiled into graphs
represented essentially by linked lists in patterns/eyes.c
.
Each actual eye space as it occurs on the board is also compiled into a graph. Half eyes are handled as follows. Referring to the example
XXOOOOO XOa...O XbOOOOO XXXXXX
repeated from the preceding discussion, the vertex at b
is
added to the eyespace as a marginal vertex. The adjacency
condition in the graph is a macro (in optics.c
): two
vertices are adjacent if they are physically adjacent,
or if one is a half eye and the other is its key point.
In recognize_eyes, each such graph arising from an actual eyespace is
matched against the graphs in eyes.c
. If a match is found, the
result of the local game is known. If a graph cannot be matched, its
local game is assumed to be {2|2}.
A HALF EYE is a pattern where an eye may or may not materialize,
depending on who moves first. Here is a half eye for O
:
OOOX O..X OOOX
A FALSE EYE is a cave which cannot become an eye. Here is are
two examples of false eyes for O
:
OOX OOX O.O O.OO XOO OOX
We describe now the topological algorithm used to find half eyes and false eyes.
False eyes and half eyes can locally be characterized by the status of the diagonal intersections from an eye space. For each diagonal intersection, which is not within the eye space, there are three distinct possibilities:
X
) stone, which cannot be captured.
X
can safely play there, or occupied
by an X
stone that can both be attacked and defended.
O
stone, an X
stone that can be attacked
but not defended, or it's empty and X
cannot safely play there.
We give the first possibility a value of two, the second a value of one, and the last a value of zero. Summing the values for the diagonal intersections, we have the following criteria:
If the eye space is on the edge, the numbers above should be decreased by 2. An alternative approach is to award diagonal points which are outside the board a value of 1. To obtain an exact equivalence we must however give value 0 to the points diagonally off the corners, i.e. the points with both coordinates out of bounds.
The algorithm to find all topologically false eyes and half eyes is:
For all eye space points with at most one neighbor in the eye space, evaluate the status of the diagonal intersections according to the criteria above and classify the point from the sum of the values.
The following situation is rare but special enough to warrant separate attention:
OOOOXX OXaX.. ------
Here a
may be characterized by the fact that it is adjacent
to O's eyespace, and it is also adjacent to an X group which cannot
be attacked, but that an X move at 'a' results in a string with only
one liberty. We call this a false margin.
For the purpose of the eye code, O's eyespace should be parsed
as (X)
, not (X!)
.
optics.c
Here are the public functions in optics.c
. The statically
declared functions are documented in the source code.
void make_domains(struct eye_data b_eye[MAX_BOARD][MAX_BOARD], struct eye_data w_eye[MAX_BOARD][MAX_BOARD])
This function is called from make_dragons(). It marks the black and white domains (eyeshape regions) and collects some statistics about each one.
void originate_eye(int i, int j, int m, int n, int *esize, int *msize, struct eye_data eye[MAX_BOARD][MAX_BOARD])
originate_eye(i, j, i, j, *size) creates an eyeshape with origin (i, j). the last variable returns the size. The repeated variables (i, j) are due to the recursive definition of the function.
static void print_eye(struct eye_data eye[MAX_BOARD][MAX_BOARD], int i, int j)
Print debugging data for the eyeshape at (i,j). Useful with GDB.
void compute_eyes(int i, int j, int *max, int *min,
int *attacki, int *attackj, struct eye_data eye[MAX_BOARD][MAX_BOARD],
int add_moves, int color)
Given an eyespace with origin (i,j), this function computes the minimum and maximum numbers of eyes the space can yield. Ifadd_moves==1
, this function may add a move_reason forcolor
at a vital point which is found by the function. Ifadd_moves==0
, setcolor==EMPTY
.
void compute_eyes_pessimistic(int i, int j, int *max, int *min, int *pessimistic_min, int *attacki, int *attackj, int *defendi, int *defendj, struct eye_data eye[MAX_BOARD][MAX_BOARD], struct half_eye_data heye[MAX_BOARD][MAX_BOARD])
This function works like compute_eyes(), except that it also gives a pessimistic view of the chances to make eyes. Since it is intended to be used from the owl code, the option to add move reasons has been removed.
void propagate_eye (int i, int j, struct eye_data eye[MAX_BOARD][MAX_BOARD])
Copies the data at the origin (i, j) to the rest of the eye (certain fields only).
static int recognize_eye(int i, int j, int *ai, int *aj, int *di, int *dj, int *max, int *min, struct eye_data eye[MAX_BOARD][MAX_BOARD], struct half_eye_data heye[MAX_BOARD][MAX_BOARD], int add_moves, int color)
Declared static but documented here because of its importance. The life code supplies an alternative version of this function calledrecognize_eye2()
. Here(i,j)
is the origin of an eyespace. Returns 1 if there is a pattern ineyes.c
matching the eyespace, or 0 if no match is found. If there is a key point for attack,(*ai, *aj)
are set to its location, or(-1, -1)
if there is none. Similarly(*di, *dj)
is the location of a vital defense point.*min
and*max
are the minimum and maximum number of eyes that can be made in this eyespace respectively. Vital attack/defense points exist if and only if*min != *max
. Ifadd_moves==1
, this function may add a move_reason for (color) at a vital point which is found by the function. Ifadd_moves==0
, setcolor==EMPTY
.
void add_half_eye(int m, int n, struct eye_data eye[MAX_BOARD][MAX_BOARD], struct half_eye_data hey[MAX_BOARD][MAX_BOARD])
This function adds a half eye or false eye to an eye shape.
int eye_space(int i, int j)
Used from constraints to identify eye spaces, primarily for late endgame moves. This returns true if the location is an eye space of either color.
int proper_eye_space(int i, int j)
Used from constraints to identify proper eye spaces, primarily for late endgame moves. Returns true if the location is an eye space of either color and is not marginal.
int marginal_eye_space(int i, int j)
Used from constraints to identify marginal eye spaces, primarily for late endgame moves. Returns true if the location is a marginal eye space of either color.
void make_proper_eye_space(int i, int j, int color)
Turn a marginal eye space into a proper eye space.
void remove_half_eye(int m, int n, int color)
Remove a halfeye from an eye shape.
void remove_eyepoint(int m, int n, int color)
Remove an eye point. This function can only be used before the segmentation into eyespaces.
int topological_eye(int m, int n, int color, int *ai, int *aj, int *di, int *dj, struct eye_data b_eye[MAX_BOARD][MAX_BOARD], struct eye_data w_eye[MAX_BOARD][MAX_BOARD], struct half_eye_data heye[MAX_BOARD][MAX_BOARD])
See See Eye Topology. Evaluate the eye space at(m, n)
topologically (see Eye Topology). Returns 2 or less if(m, n)
is a proper eye for (color); 3 if(m, n)
is a half eye; 4 if(m, n)
is a false eye.(*ai, *aj)
and(*di, *dj)
return the coordinates of an unsettled diagonal intersection, or an attack or defense point of defense of an opponent stone occupying a diagonal intersection.
int evaluate_diagonal_intersection(int m, int n, int color, int *vitali, int *vitalj)
Evaluate an intersection which is diagonal to an eye space (see Eye Topology). Returns 0 if the opponent cannot safely play at the vertex; Returns 1 if empty and the opponent can safely play on it, or if the vertex is occupied by an opponent stone which can be either attacked or defended. Returns 2 if safely occupied by the opponent. Exception: if one coordinate is off the board, returns 1; if both are off the board, returns 0. This guarantees correct behavior for diagonal intersections of points on the edge or in the corner. If the return value is 1,(*vitali, *vitalj)
returns(m, n)
if the vertex is empty, or the vital point of defense if it is occupied by an opponent stone.
connections.c
Several pattern databases are in the patterns directory. This chapter
primarily discusses the patterns in patterns.db
, patterns2.db
,
and the pattern files hoshi.db
etc. which are compiled from the SGF
files hoshi.sgf
(see Joseki Compiler). There is no essential
difference between these files, except that the ones in patterns.db
and
patterns2.db
are hand written. They are concatenated before being
compiled by mkpat
into patterns.c
. The purpose of the separate
file patterns2.db
is that it is handy to move patterns into a new
directory in the course of organizing them. The patterns in patterns.db
are more disorganized, and are slowly being moved to patterns2.db
.
During the execution of genmove()
, the patterns are matched in
shapes.c
in order to find move reasons.
The same basic pattern format is used by attack.db
, defense.db
,
conn.db
, apats.db
and dpats.db
. However these patterns
are used for different purposes. These databases are discussed in other parts
of this documentation. The patterns in eyes.db
are entirely different
and are documented elsewhere (see Eyes).
The patterns described in the databases are ascii representations, of the form:
Pattern EB112
?X?.? jump under O.*oo O.... o.... ----- :8,ed,NULL
Here 'O' marks a friendly stone, 'X' marks an enemy stone, '.' marks an empty vertex, '*' marks O's next move, 'o' marks a square either containing 'O' or empty but not X. (The symbol 'x', which does not appear in this pattern, means 'X' or '.'.) Finally '?' Indicates a location where we don't care what is there, except that it cannot be off the edge of the board.
The line of -'s along the bottom in this example is the edge of the board itself--this is an edge pattern. Corners can also be indicated. Elements are not generated for '?' markers, but they are not completely ignored - see below.
The line beginning :
describes various attributes of the pattern, such
as its symmetry and its class. Optionally, a function called a
"helper" can be provided to assist the matcher in deciding whether
to accept move. Most patterns do not require a helper, and this field
is filled with NULL.
The matcher in matchpat.c
searches the board for places where this
layout appears on the board, and the callback function
shapes_callback()
in shapes.c
registers the appropriate move
reasons.
After the pattern, there is some supplementary information in the format:
:trfno, classification, [values], helper_function
Here trfno represents the number of transformations of the pattern to consider, usually 8 (no symmetry, for historical reasons), or one of | \ / - + X, where the line represents the axis of symmetry. (E.g. | means symmetrical about a vertical axis.)
The above pattern could equally well be written on the left edge:
|?X?.? |O.*oo |O.... |o.... :8,ed,NULL
The program mkpat
is capable of parsing patterns written this
way, or for that matter, on the top or right edges, or in any
of the four corners. As a matter of convention all the edge patterns
in patterns.db
are written on the bottom edge or in the lower left
corners. In the patterns/
directory there is a program called
transpat
which can rotate or otherwise transpose patterns.
This program is not built by default--if you think you need it,
make transpat
in the patterns/
directory and
consult the usage remarks at the beginning of patterns/transpat.c
.
The attribute field in the :
line of a pattern consists of a sequence
of zero or more of the following characters, each with a different
meaning. The attributes may be roughly classified as constraints,
which determine whether or not the pattern is matched, and actions,
which describe what is to be done when the pattern is matched, typically
to add a move reason.
s
Safety of the move is not checked. This is appropriate for sacrifice patterns. If this classification is omitted, the matcher requires that the stone played cannot be trivially captured. Even with s classification, a check for legality is made, though.
n
In addition to usual check that the stone played cannot be trivially captured, it is also confirmed that an opponent move here could not be captured.
O
It is checked that every friendly (O
) stone of the pattern belongs to a dragon which has matcher_status (see Dragons) ALIVE or UNKNOWN. The CRITICAL matcher status is excluded. It is possible for a string to have ALIVE matcher_status and still be tactically critical, since it might be amalgamated into an ALIVE dragon, and the matcher status is constant on the dragon. Therefore, an additional test is performed: if the pattern contains a string which is tactically critical, and if*
does not rescue it, the pattern is rejected.
o
It is checked that every friendly (O
) stone of the pattern
belongs to a dragon which is classified as DEAD or UNKNOWN.
X
It is checked that every opponent (X
) stone of the pattern belongs to a dragon with matcher_status ALIVE, UNKNOWN or CRITICAL. Note that there is an asymmetry withO
patterns, where CRITICAL dragons are rejected.
x
It is checked that every opponent (X
) stone of the pattern
belongs to a dragon which is classified as DEAD or UNKNOWN
C
If two or more distinct O dragons occur in the pattern, the move is given the move reasons that it connects each pair of dragons. An exception is made for dragons where the underlying worm can be tactically captured and is not defended by the considered move.
c
Add strategical defense move reason for all our dragons and a small shape bonus. This classification is appropriate for weak connection patterns.
B
If two or more distinct X dragons occur in the pattern, the move is given the move reasons that it cuts each pair of dragons.
b
The move secures territory by blocking it from intrusion.
e
The move makes territory by expanding, e.g. along the edge.
E
The move attempts increase influence and create/expand a moyo.
d
The move strategically defends all O dragons in the pattern, except those that can be tactically captured and are not tactically defended by this move. If any O dragon should happen to be perfectly safe already, this only reflects in the move reason being valued to zero.
a
The move strategically attacks all X dragons in the pattern.
J
Standard joseki move. Unless there is an urgent move on the board these moves are made as soon as they can be. This is equivalent to adding thed
anda
classifications together with a shape bonus of 5 and a minimum accepted value of 25.
j
Slightly less urgent joseki move. These moves will be made after those with theJ
classification. This is equivalent to adding thee
andE
classifications together with a minimum accepted value of 22.
t
Minor joseki move (tenuki OK). This is equivalent to adding thee
andE
classifications together with a minimum accepted value of 18.
U
Urgent joseki move (never tenuki). This is equivalent to thed
anda
classifications together with a shape bonus of 20 and a minimum accepted value of 50.
A commonly used class is OX (which rejects pattern if either side
has dead stones). The string -
may be used as a placeholder. (In
fact any characters other than the above and ,
are ignored.)
The types o and O could conceivably appear in a class, meaning it applies only to UNKNOWN. X and x could similarly be used together. All classes can be combined arbitrarily.
The second third field in the :
line of a pattern
is optional and of the form value1(x),value2(y),...
. The available set
of values are as follows.
terri(x)
Forces the territorial value of the move to be at most x
minterri(x)
:
Forces the territorial value of the move to be at least x
maxterri(x)
:
Forces the territorial value of the move to be at most x.
value(x)
:
Forces the final value of the move to be at least x.
minvalue(x)
maxvalue(x)
:
Forces the final value of the move to be at last/most x.
shape(x)
:
Adds x to the move's shape value.
followup(x)
:
Adds x to the move's followup value.
The meaning of these values is documented in See Move Generation.
Helper functions can be provided to assist the matcher in deciding
whether to accept a pattern, register move reasons, and setting
various move values. The helper is supplied with the compiled pattern
entry in the table, and the (absolute) position on the board of the
*
point.
One difficulty is that the helper must be able to cope with all the possible transformations of the pattern. To help with this, the OFFSET macro is used to transform relative pattern coordinates to absolute board locations.
The actual helper functions are in helpers.c
. They are declared
in patterns.h
.
As an example to show how to write a helper function, we consider
wedge_helper
. (This helper does not exist anymore but has been
replaced by a constraint, discussed in the following section. Due to
its simplicity it's still a good example.) The helper begins with a
comment:
/* ?O. ?Ob .X* aXt ?O. ?Oc :8,C,wedge_helper */
The image on the left is the actual pattern. On the right we've taken this image and added letters to label (ti, tj), (ai, aj) and (bi, bj). Of course t is always at *, the point where GNU Go will move if the pattern is adopted.
int wedge_helper (ARGS) { int ai, aj, bi, bj, ci, cj; int other = OTHER_COLOR(color); int success = 0; OFFSET(0, -2, ai, aj); OFFSET(-1, 0, bi, bj); OFFSET(1, 0, ci, cj); if (TRYMOVE(ti, tj, color)) { if (TRYMOVE(ai, aj, other)) { if (!p[ai][aj] || attack(ai, aj, NULL, NULL)) success = 1; else if (TRYMOVE(bi, bj, color)) { if (!safe_move(ci, cj, other)) success = 1; popgo(); } popgo(); } popgo(); } return success; }
The OFFSET
lines tell GNU Go the positions of the three stones at
a=(ai,aj)
, b=(bi,bj)
, and c=(ci,cj)
. To decide
whether the pattern guarantees a connection, we do some reading. First
we use the TRYMOVE
macro to place an O at t and let X draw back
to a. Then we try whether O can capture these stones by calling
attack()
. The test if there is a stone at a before calling
attack()
is in this position not really necessary but it's good
practice to do so, because if the attacked stone should happen to
already have been captured while placing stones, GNU Go would crash with
an assertion failure.
If this attack fails we let O connect at b and use the safe_move()
function to examine whether a cut by X at c could be immediately
captured. Before we return the result we need to remove the stones we
placed from the reading stack. This is done with the function popgo()
.
In addition to the hand-written helper functions in helpers.c
, GNU Go
can automatically generate helper functions from a diagram with labels
and an expression describing a constraint. The constraint diagram,
specifying the labels, is placed below the ":" line and the constraint
expression is placed below the diagram on line starting with a ";".
Constraints can only be used to accept or reject a pattern. If the
constraint evaluates to zero (false) the pattern is rejected,
otherwise it's accepted (still conditioned on passing all other tests
of course). To give a simple example we consider a connection pattern.
Pattern Conn311
O*. ?XO :8,C,NULL O*a ?BO ;oplay_attack_either(*,a,a,B)
Here we have given the label a
to the empty spot to the right of the
considered move and the label B
to the X
stone in the pattern. In
addition to these, *
can also be used as a label. A label may be any
lowercase or uppercase ascii letter except OoXxt. By convention we use
uppercase letters for X stones and lowercase for O stones and empty
intersections. When labeling a stone that's part of a larger string in
the pattern, all stones of the string should be marked with the label.
(These conventions are not enforced by the pattern compiler, but to
make the database consistent and easy to read they should be
followed.)
The labels can now be used in the constraint expression. In this example we have a reading constraint which should be interpreted as "Play an O stone at * followed by an X stone at a. Accept the pattern if O now can capture either at a or at B (or both strings)."
The functions that are available for use in the constraints are listed
in the section `Autohelpers Functions' below. Technically the
constraint expression is transformed by mkpat into an automatically
generated helper function in patterns.c
. The functions in the
constraint are replaced by C expressions, often functions calls. In
principle any valid C code can be used in the constraints, but there
is in practice no reason to use anything more than boolean and
arithmetic operators in addition to the autohelper functions.
Constraints can span multiple lines, which are then concatenated.
As a complement to the constraints, which only can accept or reject a pattern, one can also specify an action to perform when the pattern has passed all tests and finally has been accepted.
Example:
Pattern EJ4 ...*. continuation .OOX. ..XOX ..... ----- :8,Ed,NULL ...*. never play a here .OOX. .aXOX ..... ----- >antisuji(a)
The line starting with >
is the action line. In this case it tells
the move generation that the move at a should not be considered,
whatever move reasons are found by other patterns. The action line
uses the labels from the constraint diagram. Both constraint and
action can be used in the same pattern. If the action only needs to
refer to *
, no constraint diagram is required. Like constraints,
actions can span multiple lines.
The autohelper functions are translated into C code by the program in
mkpat.c
. To see exactly how the functions are implemented,
consult the autohelper function definitions in that file. Autohelper
functions can be used in both constraint and action lines.
lib(x)
lib2(x)
lib3(x)
lib4(x)
Number of first, second, third, and fourth order liberties of a worm respectively. See Worms and Dragons, the documentation on worms for definitions.
xlib(x)
olib(x)
The number of liberties that an enemy or own stone, respectively, would obtain if played at the empty intersection x.
xcut(x)
ocut(x)
Calls cut_possible
(see General Utilities) to determine
whether X
or O
can cut at the empty intersection x.
ko(x)
True if x is either a stone or an empty point involved in a ko position.
status(x)
The matcher status of a dragon. status(x) returns an integer that can have the
values ALIVE
, UNKNOWN
, CRITICAL
, or DEAD
(see Worms and Dragons).
alive(x)
unknown(x)
critical(x)
dead(x)
Each function true if the dragon has the corresponding matcher status and false otherwise (see Worms and Dragons).
status(x)
Returns the status of the dragon at x
(see Worms and Dragons).
genus(x)
The number of eyes of a dragon. It is only meaningful to compare this value against 0, 1, or 2.
xarea(x)
oarea(x)
xmoyo(x)
omoyo(x)
xterri(x)
oterri(x)
Functions related to various kinds of influence and territory
estimations, as described in See Moyo. xarea(x) evaluates to true if
x is either a living enemy stone or an empty point within his "area".
oarea(x)
is analogous but with respect to our stones and area.
The main difference between area, moyo, and terri is that area is a
very far reaching kind of influence, moyo gives a more realistic
estimate of what may turn in to territory, and terri gives the points
that already are believed to be secure territory.
weak(x)
True for a dragon that is perceived as weak. The definition of weak is given in See Moyo.
attack(x)
defend(x)
Results of tactical reading. attack(x) is true if the worm can be captured, defend(x) is true if there also is a defending move. Please notice that defend(x) will return false if there is no attack on the worm.
safe_xmove(x)
safe_omove(x)
True if an enemy or friendly stone, respectively, can safely be played at x. By safe it is understood that the move is legal and that it cannot be captured right away.
legal_xmove(x)
legal_omove(x)
True if an enemy or friendly stone, respectively, can legally be played at x.
o_somewhere(x,y,z, ...) x_somewhere(x,y,z, ...)
True if O (respectively X) has a stone at one of the labelled vertices.
In the diagram, these vertices should be marked with a ?
.
odefend_against(x,y) xdefend_against(x,y)
True if an own stone at x would stop the enemy from safely playing at y, and conversely for the second function.
does_defend(x,y)
does_attack(x,y)
True if a move at x defends/attacks the worm at y. For defense a move of the same color as y is tried and for attack a move of the opposite color.
xplay_defend(a,b,c,...,z)
oplay_defend(a,b,c,...,z)
xplay_attack(a,b,c,...,z)
oplay_attack(a,b,c,...,z)
These functions make it possible to do more complex reading experiments in the constraints. All of them work so that first the sequence of moves a,b,c,... is played through with alternating colors, starting with X or O as indicated by the name. Then it is tested whether the worm at z can be attacked or defended, respectively. It doesn't matter who would be in turn to move, a worm of either color may be attacked or defended. For attacks the opposite color of the string being attacked starts moving and for defense the same color starts. The defend functions return true if the worm cannot be attacked in the position or if it can be attacked but also defended. The attack functions return true if there is a way to capture the worm, whether or not it can also be defended. If there is no stone present at z after the moves have been played, it is assumed that an attack has already been successful or a defense has already failed. If some of the moves should happen to be illegal, typically because it would have been suicide, the following moves are played as if nothing has happened and the attack or defense is tested as usual. It is assumed that this convention will give the relevant result without requiring a lot of special cases.
The special label ?
can be used to represent a tenuki.
Thus oplay_defend(a,?,b,c)
tries moves by O
at a
and
b
, as if X
plays the second move in another part of
the board, then asks if c
can be defended. The tenuki cannot
be the first move of the sequence, nor does it need to be:
instead of oplay_defend(?,a,b,c)
you can use
xplay_defend(a,b,c)
.
xplay_defend_both(a,b,c,...,y,z)
oplay_defend_both(a,b,c,...,y,z)
xplay_attack_either(a,b,c,...,y,z)
oplay_attack_either(a,b,c,...,y,z)
These functions are similar to the previous ones. The difference is that the last *two* arguments denote worms to be attacked or defended simultaneously. Obviously y and z must have the same color. If either location is empty, it is assumed that an attack has been successful or a defense has failed. The typical use for these functions is in cutting patterns, where it usually suffices to capture either cutstone.
The function xplay_defend_both
plays alternate moves
beginning with an X at a
. Then it passes the last
two arguments to defend_both
in
engine/utils.c
. This function checks to determine
whether the two strings can be simultaneously defended.
The function xplay_attack_either
plays alternate
moves beginning with an X move at a
. Then it passes
the last two arguments to attack_either
in
engine/utils.c
. This function looks for a move
which captures at least one of the two strings. In its
current implementation attack_either
only looks
for uncoordinated attacks and would thus miss a double
atari.
xplay_break_through(a,b,c,...,x,y,z)
oplay_break_through(a,b,c,...,x,y,z)
These functions are used to set up a position like
.O. .y. OXO xXz
and X aims at capturing at least one of x, y, and z. If this succeeds 1 is returned. If it doesn't, X tries instead to cut through on either side and if this succeeds, 2 is returned. Of course the same shape with opposite colors can also be used.
Important notice: x, y, and z must be given in the order they have in the diagram above, or any reflection and/or rotation of it.
seki_helper(x)
Checks whether the string at x
can attack any surrounding
string. If so, return false as the move to create a seki (probably)
wouldn't work.
threaten_to_save(x)
Calls add_followup_value
to add as a move reason a conservative
estimate of the value of saving the string x
by capturing one opponent
stone.
area_stone(x)
Returns the number of stones in the area around x
.
area_space(x)
Returns the amount of space in the area around x
.
eye(x)
proper_eye(x)
marginal_eye(x)
True if x is an eye space for either color, a non-marginal eye space for either color, or a marginal eye space for either color, respectively.
antisuji(x)
Tell the move generation that x is a substandard move that never should be played.
same_dragon(x,y) same_worm(x,y)
Return true if x and y are the same dragon or worm respectively.
dragonsize(x)
wormsize(x)
Number of stones in the indicated dragon or worm.
add_connect_move(x,y)
add_cut_move(x,y)
add_attack_either_move(x,y)
add_defend_both_move(x,y)
Explicitly notify the move generation about move reasons for the move in the pattern.
halfeye(x)
Returns true if the empty intersection at x
is a half eye.
remove_attack(x)
Inform the tactical reading that a supposed attack does in fact not work.
potential_cutstone(x)
True if cutstone2 field from worm data is larger than one. This indicates that saving the worm would introduce at least two new cutting points.
not_lunch(x,y)
Prevents the misreporting of x
as lunch for y
.
For example, the following pattern tells GNU Go that even
though the stone at a
can be captured, it should not
be considered "lunch" for the dragon at b
, because
capturing it does not produce an eye:
XO| ba| O*| O*| oo| oo| ?o| ?o| > not_lunch(a,b)
vital_chain(x)
Calls vital_chain
to determine whether capturing
the stone at x
will result in one eye for an adjacent
dragon. The current implementation just checks that the stone
is not a singleton on the first line.
amalgamate(x,y)
Amalgamate (join) the dragons at x
and y
(see Worms and Dragons).
amalgamate_most_valuable(x,y,z)
Called when (x,y,z) point to three (preferably distinct) dragons, in situations such as this:
.O.X X*OX .O.X
In this situation, the opponent can play at *, preventing
the three dragons from becoming connected. However O
can decide which cut to allow. The helper amalgamates the
dragon at y
with either x
or z
,
whichever is largest.
make_proper_eye(x)
This autohelper should be called when x
is an eyespace
which is misidentified as marginal. It is reclassified as
a proper eyespace (see Eye Space).
remove_halfeye(x)
Remove a half eye from the eyespace. This helper should not be run after
make_dragons
is finished, since by that time the eyespaces have
already been analyzed.
remove_eyepoint(x)
Remove an eye point. This function can only be used before the segmentation into eyespaces.
owl_topological_eye(x,y)
Here x
is an empty intersection which may be an
eye or half eye for some dragon, and y
is a
stone of the dragon, used only to determine the color
of the eyespace in question. Returns the sum of the values
of the diagonal intersections, relative to x
, as
explained in See Eye Topology, equal to 4 or more if the
eye at x
is false, 3 if it is a half eye, and 2 if it
is a true eye.
owl_escape_value(x)
Returns the escape value at x
. This is only useful in owl
attack and defense patterns and only if the
--alternative_escape
option is turned on. Otherwise 0 is
returned.
The patterns in attack.db
and defense.db
are used to assist the
tactical reading in finding moves that attacks or defends worms. The
matching is performed during make_worms()
, at the time when the
tactical status of all worms is decided. None of the classes described
above are useful in these databases, instead we have two other
classes.
D : For each O worm in the pattern that can be tactically captured (worm[m][n].attack_code != 0), the move at*
is tried. If it is found to defend the stone, this is registered as a reason for the move * and the defense point of the worm is set to*
. A : For each X worm in the pattern, it's tested whether the move at * captures the worm. If that is the case, this is registered as a reason for the move at*
. The attack point of the worm is set to * and if it wasn't attacked before, a defense is searched for.
Furthermore, A patterns can only be used in attack.db
and D patterns
only in defense.db
. Unclassified patterns may appear in these
databases, but then they must work through actions to be effective.
The patterns in conn.db
are used for helping make_dragons()
amalgamate worms into dragons and to some extent for modifying eye spaces.
The patterns in this database use the classifications B
,
C
, and e
. B
patterns are used for finding cutting points,
where amalgamation should not be performed, C
patterns are used for
finding existing connections, over which amalgamation is to be done, and
e
patterns are used for modifying eye spaces and reevaluating lunches.
There are also some patterns without classification, which use action lines to
have an impact. These are matched together with the C
patterns. Further
details and examples can be found in See Worms and Dragons.
We will illustrate these databases by example. In this situation:
XOO O.O ...
X
cannot play safely at the cutting point, so the O
dragons
are to be amalgamated. Two patterns are matched here:
Pattern CC204 O . O :+,C O A O ;!safe_xmove(A) && !ko(A) && !xcut(A) Pattern CC205 XO O. :\,C AO OB ;attack(A) || (!safe_xmove(B) && !ko(B) && !xcut(B))
The constraints are mostly clear. For example the second
pattern should not be matched if the X
stone cannot
be attacked and X
can play safely at B
, or
if B
is a ko. The constraint !xcut(B)
means
that connection has not previously been inhibited by
find_cuts
. For example consider this situation:
OOXX O.OX X..O X.OO
The previous pattern is matched here twice, yet X can push in and break one of the connections. To fix this, we include a pattern:
Pattern CB11 ?OX? O!OX ?*!O ??O? :8,B ?OA? OaOB ?*bO ??O? ; !attack(A) && !attack(B) && !xplay_attack(*,a,b,*) && !xplay_attack(*,b,a,*)
After this pattern is found, the xcut
autohelper macro will return
true at any of the points *
, a
and b
. Thus the
patterns CB204 and CB205 will not be matched, and the dragons will
not be amalgamated.
Here are the public functions in connections.c
.
static void cut_connect_callback(int m, int n, int color,
struct pattern *pattern, int ll, void *data)
Try to match all (permutations of) connection patterns at (m,n). For each match, if it is a B pattern, set cutting point in worm data structure and make eye space marginal for the connection inhibiting entries of the pattern. If it is a C pattern, amalgamate the dragons in the pattern.
void find_cuts(void)
Find cutting points which should inhibit amalgamations and sever
the adjacent eye space. This goes through the connection database
consulting only patterns of type B. When such a function is found,
the function cut_connect_callback
is invoked.
void find_connections(void)
Find explicit connection patterns and amalgamate the involved dragons.
This goes through the connection database consulting patterns except those of
type B, E or e. When such a function is found, the function
cut_connect_callback
is invoked.
Find explicit connection patterns and amalgamate the involved dragons.
This goes through the connection database consulting only patterns
of type E (see Connections Database). When such a function is found, the
function cut_connect_callback
is invoked.
Find explicit connection patterns and amalgamate the involved dragons.
This goes through the connection database consulting only patterns
of type e (see Connections Database). When such a function is found, the
function cut_connect_callback
is invoked.
Since the pattern databases, together with the valuation of move reasons, decide GNU Go's personality, much time can be devoted to "tuning" them. Here are some suggestions.
If you want to experiment with modifying the pattern database, invoke with the -a option. This will cause every pattern to be evaluated, even when some of them may be skipped due to various optimizations.
You can obtain a Smart Go Format (SGF) record of your game in at least two different ways. One is to use CGoban to record the game. You can also have GNU Go record the game in Smart Go Format, using the -o option. It is best to combine this with -a. Do not try to read the SGF file until the game is finished and you have closed the game window. This does not mean that you have to play the game out to its conclusion. You may close the CGoban window on the game and GNU Go will close the SGF file so that you can read it.
If you record a game in SGF form using the -o option, GNU Go will add labels to the board to show all the moves it considered, with their values. This is an extremely useful feature, since one can see at a glance whether the right moves with appropriate weights are being proposed by the move generation.
First, due to a bug of unknown nature, it occasionally happens
that GNU Go will not receive the SIGTERM
signal from CGoban that it
needs to know that the game is over. When this happens, the SGF file
ends without a closing parenthesis, and CGoban will not open the
file. You can fix the file by typing:
echo ")" >>[filename]
at the command line to add this closing parenthesis. Or you could add the ) using an editor.
Move values exceeding 99 (these should be rare) can be displayed by CGoban but you may have to resize the window in order to see all three digits. Grab the lower right margin of the CGoban window and pull it until the window is large. All three digits should be visible.
If you are playing a game without the -o option and you wish to analyze a move, you may still use CGoban's "Save Game" button to get an SGF file. It will not have the values of the moves labelled, of course.
Once you have a game saved in SGF format, you can analyze any particular move by running:
gnugo -l [filename] -L [move number] -t -a -w
to see why GNU Go made that move, and if you make changes to the pattern database and recompile the program, you may ask GNU Go to repeat the move to see how the behavior changes. If you're using emacs, it's a good idea to run GNU Go in a shell in a buffer (M-x shell) since this gives good navigation and search facilities.
Instead of a move number, you can also give a board coordinate to -L in order to stop at the first move played at this location. If you omit the -L option, the move after those in the file will be considered.
If a bad move is proposed, this can have several reasons. To begin with, each move should be valued in terms of actual points on the board, as accurately as can be expected by the program. If it's not, something is wrong. This may have two reasons. One possibility is that there are reasons missing for the move or that bogus reasons have been found. The other possibility is that the move reasons have been misevaluated by the move valuation functions. Tuning of patterns is with a few exceptions a question of fixing the first kind of problems.
If there are bogus move reasons found, search through the trace output for the pattern that is responsible. (Some move reasons, e.g. most tactical attack and defense, do not originate from patterns. If no pattern produced the bogus move reason, it is not a tuning problem.) Probably this pattern was too general or had a faulty constraint. Try to make it more specific or correct bugs if there were any. If the pattern and the constraint looks right, verify that the tactical reading evaluates the constraint correctly. If not, this is either a reading bug or a case where the reading is too complicated for GNU Go.
If a connecting move reason is found, but the strings are already
effectively connected, there may be missing patterns in conn.db
.
Similarly, worms may be incorrectly amalgamated due to some too
general or faulty pattern in conn.db
. To get trace output from the
matching of patterns in conn.db
you need to add a second -t option.
If a move reason is missing, there may be a hole in the database. It could also be caused by some existing pattern being needlessly specific, having a faulty constraint, or being rejected due to a reading mistake. Unless you are familiar with the pattern databases, it may be hard to verify that there really is a pattern missing. Look around the databases to try to get a feeling for how they are organized. (This is admittedly a weak point of the pattern databases, but the goal is to make them more organized with time.) If you decide that a new pattern is needed, try to make it as general as possible, without allowing incorrect matches, by using proper classification from among snOoXx and constraints. The reading functions can be put to good use. The reason for making the patterns as general as they can be is that we need a smaller number of them then, which makes the database much easier to maintain. Of course, if you need too complicated constraints, it's usually better to split the pattern.
If a move has the correct set of reasons but still is misevaluated,
this is usually not a tuning problem. There are, however, some
possibilities to work around these mistakes with the use of patterns.
In particular, if the territorial value is off because delta_terri()
give strange results, the (min)terri and maxterri values can be set by
patterns as a workaround. This is typically done by the endgame
patterns, where we can know the (minimum) value fairly well from the
pattern. If it should be needed, (min)value and maxvalue can be used
similarly. These possibilities should be used conservatively though,
since such patterns are likely to become obsolete when better (or at
least different) functions for e.g. territory estimation are being
developed.
In order to choose between moves with the same move reasons, e.g. moves that connect two dragons in different ways, patterns with a nonzero shape value should be used. These should give positive shape values for moves that give good shape or good aji and negative values for bad shape and bad aji. Notice that these values are additive, so it's important that the matches are unique.
Sente moves are indicated by the use of the pattern followup value. This can usually not be estimated very accurately, but a good rule is to be rather conservative. As usual it should be measured in terms of actual points on the board. These values are also additive so the same care must be taken to avoid unintended multiple matches.
You can also get a visual display of the dragons using the -T option. The default GNU Go configuration tries to build a version with color support using either curses or the ansi escape sequences. You are more likely to find color support in rxvt than xterm, at least on many systems, so we recommend running:
gnugo -l [filename] -L [move number] -T
in an rxvt window. If you do not see a color display, and if your host is a GNU/Linux machine, try this again in the Linux console.
Worms belonging to the same dragon are labelled with the same letters.
The colors indicate the value of the field dragon.safety
, which
is set in moyo.c
.
Green: GNU Go thinks the dragon is alive
Yellow: Status unknown
Blue: GNU Go thinks the dragon is dead
Red: Status critical (1.5 eyes) or weak by the algorithm
in moyo.c
If you want to get the same game over and over again, you can eliminate the randomness in GNU Go's play by providing a fixed random seed with the -r option.
The pattern code in GNU Go is fairly straightforward conceptually, but because the matcher consumes a significant part of the time in choosing a move, the code is optimized for speed. Because of this there are implementation details which obscure things slightly.
In GNU Go, the ascii .db
files are precompiled into tables (see
patterns.h
) by a standalone program mkpat.c
, and the resulting
.c
files are compiled and linked into the main gnugo executable.
Each pattern is compiled to a header, and a sequence of elements,
which are (notionally) checked sequentially at every position and
orientation of the board. These elements are relative to the pattern
'anchor' (or origin). One X or O stone is (arbitrarily) chosen to
represent the origin of the pattern. (We cannot dictate one or the
other since some patterns contain only one colour or the other.) All
the elements are in co-ordinates relative to this position. So a
pattern matches "at" board position (m,n,o) if the the pattern anchor
stone is on (m,n), and the other elements match the board when the
pattern is transformed by transformation number o
. (See below for
the details of the transformations, though these should not be
necessary)
In general, each pattern must be tried in each of 8 different
permutations, to reflect the symmetry of the board. But some
patterns have symmetries which mean that it is unnecessary
(and therefore inefficient) to try all eight. The first
character after the :
can be one of 8
,|
,\
,/
,
X
, -
, +
, representing the axes of symmetry. It can also
be O
, representing symmetry under 180 degrees rotation.
transformation I - | . \ l r / ABC GHI CBA IHG ADG CFI GDA IFC DEF DEF FED FED BEH BEH HEB HEB GHI ABC IHG CBA CFI ADG IFC GDA a b c d e f g h
Then if the pattern has the following symmetries, the following are true:
| c=a, d=b, g=e, h=f - b=a, c=d, e=f, g=h \ e=a, g=b, f=c, h=d / h=a, f=b, g=c, e=d O a=d, b=c, e=h, f=g X a=d=e=h, b=c=f=g + a=b=c=d, e=f=g=h
We can choose to use transformations a,d,f,g as the unique
transformations for patterns with either |
, -
, \
, or
/
symmetry.
Thus we choose to order the transformations a,g,d,f,h,b,e,c and choose
first 2 for X
and +
, the first 4 for |
, -
,
/
, and \
, the middle 4 for O
, and all 8 for
non-symmetrical patterns.
Each of the reflection operations (e-h) is equivalent to reflection about one arbitrary axis followed by one of the rotations (a-d). We can choose to reflect about the axis of symmetry (which causes no net change) and can therefore conclude that each of e-h is equivalent to the reflection (no-op) followed by a-d. This argument therefore extends to include - and / as well as | and \.
?
until it is exactly 19 (or
whatever the current board size is) elements wide or high. Then the
pattern is quickly rejected by (ii) above if it is not at the edge. So
the example pattern above is compiled as if it was written
"example" .OO???????????????? *XX???????????????? o?????????????????? :8,80
o
is the
same as a test for 'not-X', ie not %10. So and with %01
should give 0 if it matches. Similarly x
is a test that
bit 0 is not set.
The comparisons between pattern and board are performed as 2-bit bitwise operations. Therefore they can be performed in parallel, 16-at-a-time on a 32-bit machine.
Suppose the board is layed out as follows :
.X.O....OO XXXXO..... .X..OOOOOO X.X....... ....X...O.
which is internally stored internally in a 2d array (binary)
00 10 00 01 00 00 00 00 01 01 10 10 10 10 01 00 00 00 00 00 00 10 00 00 01 01 01 01 01 01 10 00 10 00 00 00 00 00 00 00 00 00 00 00 10 00 00 00 01 00
we can compile this to a composite array in which each element stores the state of a 4x4 grid of squares :
???????? ???????? ???????? ... ??001000 00100001 10000100 ??101010 10101010 10101001 ??001000 00100000 10000001 ??001000 00100001 ... ??101010 10101010 ??001000 00100000 ??001000 10001000 ... ??100010 ... ??000000 ???????? ????????
Where '??' is off the board.
We can store these 32-bit composites in a 2d merged-board array, substituting the illegal value %11 for '??'.
Similarly, for each pattern, mkpat produces appropriate 32-bit and-value masks for the pattern elements near the anchor. It is a simple matter to test the pattern with a similar test to (5) above, but for 32-bits at a time.
GNU Go includes a joseki compiler in patterns/joseki.c
. This processes
an SGF file (with variations) and produces a sequence of patterns
which can then be fed back into mkpat. The joseki database is currently in files
in patterns/
called hoshi.sgf
, komoku.sgf
, sansan.sgf
,
mokuhazushi.sgf
and takamoku.sgf
. This division can be revised
whenever need arises.
The SGF files are transformed into the pattern database .db
format by
the program in joseki.c
. These files are in turn transformed into C
code by the program in mkpat.c
and the C files are compiled and linked
into the GNU Go binary.
Not every node in the SGF file contributes a pattern. The nodes which contribute patterns have the joseki in the upper right corner, with the boundary marked with a square mark and other information to determine the resulting pattern marked in the comments.
The intention is that the move valuation should be able to choose between the available variations by normal valuation. When this fails the primary workaround is to use shape values to increase or decrease the value. It is also possible to add antisuji variations to forbid popular suboptimal moves. As usual constraints can be used, e.g. to condition a variation on a working ladder.
The joseki format has the following components for each SGF node:
SQ
or MA
property) to decide how large part of the
board should be included in the pattern.
W
or B
property) with the natural interpretation.
If the square mark is missing or the move is a pass, no pattern is
produced for the node.
LB
property), which must be a single letter each.
If there is at least one label, a constraint diagram will be
produced with these labels.
C
property). As the first character it should have one of the
following characters to decide its classification:
U
- urgent move
S
or J
- standard move
s
or j
- lesser joseki
T
- trick move
t
- minor joseki move (tenuki OK)
0
- antisuji (A
can also be used)
In addition to this, rows starting with the following characters are recognized:
#
- Comments. These are copied into the patterns file, above the diagram.
;
- Constraints. These are copied into the patterns file, below the
constraint diagram.
>
- Actions. These are copied into the patterns file, below the
constraint diagram.
:
- Colon line. This is a little more complicated, but the colon
line of the produced patterns always start out with ":8,s" for
transformation number and sacrifice pattern class (it usually
isn't a sacrifice, but it's pointless spending time checking for
tactical safety). Then a joseki pattern class character is
appended and finally what is included on the colon line in the
comment for the SGF node.
Example: If the comment in the SGF file looks like
F :C,shape(3) ;xplay_attack(A,B,C,D,*)
the generated pattern will have a colon line
:8,sjC,shape(3)
and a constraint
;xplay_attack(A,B,C,D,*)
As an example of how to use autohelpers with the Joseki compiler, we consider an example where a Joseki is bad if a ladder fails. Assume we have the taisha and are considering connecting on the outside with the pattern
--------+ ........| ........| ...XX...| ...OXO..| ...*O...| ....X...| ........| ........|
But this is bad unless we have a ladder in our favor. To check this we add a constraint which may look like
--------+ ........| ........| ...XX...| ...OXO..| ...*OAC.| ....DB..| ........| ........| ;oplay_attack(*,A,B,C,D)
In order to accept the pattern we require that the constraint on the
semicolon line evaluates to true. This particular constraint has the
interpretation "Play with alternating colors, starting with O
,
on the intersections *
, A
, B
, and C
. Then check
whether the stone at D
can be captured." I.e. play to this position
--------+ ........| ........| ...XX...| ...OXO..| ...OOXX.| ....XO..| ........| ........|
and call attack()
to see whether the lower X
stone can be
captured. This is not limited to ladders, but in this particular case the
reading will of course involve a ladder.
The constraint diagram above with letters is how it looks in the .db
file. The joseki compiler knows how to create these from labels in
the SGF node. Cgoban
has an option to create one letter labels,
but this ought to be a common feature for SGF editors.
Thus in order to implement this example in SGF, one would add labels to the four intersections and a comment:
;oplay_attack(*,A,B,C,D)
The appropriate constraint (autohelper macro) will then be added
to the Joseki .db
file.
In this chapter, we describe the principles of the gnugo DFA
pattern matcher. The aim of this system is to permit a fast
pattern matching when it becomes time critical like in owl
module (The Owl Code). The actual version is still
experimental but is expected to be fully integrated in later
versions of gnugo. If you want to test it with version
3.0 you must run configure --enable-dfa
then recompile GNU Go (Using DFA). The basic principle
is to generate off line a finite state machine called a
Deterministic Finite State Automaton (What is a DFA)
from the pattern database and then use it at runtime to
speedup pattern matching (Pattern matching with DFA and
Incremental Algorithm).
First build the program with 'configure -enable-dfa', then type 'make' as usual.
Some .db files will be compiled into DFA's by the program mkpat. DFA are stored into C files and compiled with the engine. When a DFA is found, gnugo write "<pattern database name> -> using dfa" at startup and use the dfa to "filter" patterns. When no DFA is found, the standard pattern matcher is used.
The board is scanned following a predefined path.
The default path is a spiral starting from
the center of the pattern.
This path is used both to build the DFA and to scan the board.
This path is encoded by two arrays of integers order_i[k] and order_j[k] giving the offset where to read the values on the board.
Reading the board following a predefined path reduces the two dimentional pattern matching to a linear text searching problem. This pattern for example:
?X? .O? ?OO
scanned following the path
149 238 567 (i,j)->(i+1,j)->(i+1,j+1)->(i,j+1)->(i+2,j+0)->(i+2,j+1)->(i+2,j+2)...
gives the string "?.OX?OO??" where "?" means 'don't care'. We can forget the two dimensional patterns for a time to focus on linear patterns.
The acronym DFA means Deterministic Finite state Automaton (See http://www.eti.pg.gda.pl/~jandac/thesis/node12.html or Hopcroft & Ullman "Introduction to Language Theory" for more details). DFA are common tools in compilers design (Read Aho, Ravi Sethi, Ullman "COMPILERS: Principles, Techniques and Tools" for a complete introduction), a lot of powerfull text searching algorithm like Knuth-Morris-Pratt or Boyer-Moore algorithms are based on DFA's (See http://www-igm.univ-mlv.fr/~lecroq/string/ for a bibliography of pattern matching algorithms).
Basically, a DFA is a set of states connected by labeled transitions. The labels are the values read on the board, in gnugo these values are EMPTY, WHITE, BLACK or OUT_BOARD, denoted respectively by '.','O','X' and '#'.
The best way to represent a dfa is to draw its transition graph:
the pattern "????..X" is recognized by the following DFA:
This means that starting from state [1], if you read '.','X' or 'O' on the board, go to state [2] and so on until you reach state [5]. From state [5], if you read '.', go to state [6] otherwise go to error state [0]. And so on until you reach state [8]. As soon as you reach state [8], you recognize Pattern "????..X"
Adding a pattern like "XXo" ('o' is a wildcard for not 'X')
will transform directly the automaton
by synchronization product (Building the DFA).
Consider the following DFA:
By adding a special error state and completing each state
by a transition to error state when there is none, we transform
easily a DFA in a Complete Deterministic Finite state
Automaton (CDFA). The synchronization product
(Building the DFA) is only possible on CDFA's.
The graph of a CDFA is coded by an array of states: The 0 state is the "error" state and the start state is 1.
---------------------------------------------------- state | . | O | X | # | att ---------------------------------------------------- 1 | 2 | 2 | 9 | 0 | 2 | 3 | 3 | 3 | 0 | 3 | 4 | 4 | 4 | 0 | 5 | 6 | 0 | 0 | 0 | 6 | 7 | 0 | 0 | 0 | 7 | 0 | 0 | 8 | 0 | 8 | 0 | 0 | 0 | 0 | Found pattern "????..X" 9 | 3 | 3 | A | 0 | A | B | B | 4 | 0 | B | 5 | 5 | 5 | 0 | Found pattern "XXo" ----------------------------------------------------
To each state we associate an often empty
list of attributes which is the
list of pattern indexes recognized when this state is reached.
In 'dfa.h
' this is basically represented by two stuctures:
/* dfa state */
typedef struct state
{
int next[4]; /* transitions for EMPTY, BLACK, WHITE and OUT_BOARD */
attrib_t *att;
}
state_t;
/* dfa */
typedef struct dfa
{
attrib_t *indexes; /* Array of pattern indexes */
int maxIndexes;
state_t *states; /* Array of states */
int maxStates;
}
dfa_t;
Recognizing with a DFA is very simple
and thus very fast
(See 'scan_for_pattern()
' in the 'engine/matchpat.c
' file).
Starting from the start state, we only need to read the board following the spiral path, jump from states to states following the transitions labelled by the values read on the board and collect the patterns indexes on the way. If we reach the error state (zero), it means that no more patterns will be matched. The worst case complexity of this algorithm is o(m) where m is the size of the biggest pattern.
Here is an example of scan:
First we build a minimal dfa recognizing these patterns: "X..X", "X???", "X.OX" and "X?oX". Note that wildcards like '?','o', or 'x' give multiple out-transitions.
---------------------------------------------------- state | . | O | X | # | att ---------------------------------------------------- 1 | 0 | 0 | 2 | 0 | 2 | 3 | 10 | 10 | 0 | 3 | 4 | 7 | 9 | 0 | 4 | 5 | 5 | 6 | 0 | 5 | 0 | 0 | 0 | 0 | 2 6 | 0 | 0 | 0 | 0 | 4 2 1 7 | 5 | 5 | 8 | 0 | 8 | 0 | 0 | 0 | 0 | 4 2 3 9 | 5 | 5 | 5 | 0 | 10 | 11 | 11 | 9 | 0 | 11 | 5 | 5 | 12 | 0 | 12 | 0 | 0 | 0 | 0 | 4 2 ----------------------------------------------------
We perform the scan of the string "X..XXO...." starting from state 1:
Current state: 1, substring to scan : X..XXO....
We read an 'X' value, so from state 1 we must go to state 2.
Current state: 2, substring to scan : ..XXO....
We read a '.' value, so from state 2 we must go to state 3 and so on ...
Current state: 3, substring to scan : .XXO.... Current state: 4, substring to scan : XXO.... Current state: 6, substring to scan : XO.... Found pattern 4 Found pattern 2 Found pattern 1
After reaching state 6 where we match patterns 1,2 and 4, there is no out-transitions so we stop the matching. To keep the same match order as in the standard algorithm, the patterns indexes are collected in an array and sorted by indexes.
The most flavouring point is the building of the minimal DFA recognizing a given set of patterns. To perform the insertion of a new pattern into an already existing DFA one must completly rebuild the DFA: the principle is to build the minimal CDFA recognizing the new pattern to replace the original CDFA with its synchronised product by the new one.
We first give a formal definition: Let L be the left CDFA and R be the right one. Let B be the synchronised product of L by R. Its states are the couples (l,r) where l is a state of L and r is a state of R. The state (0,0) is the error state of B and the state (1,1) is its initial state. To each couple (l,r) we associate the union of patterns recognized in both l and r. The transitions set of B is the set of transitions (l1,r1)--a-->(l2,r2) for each symbol 'a' such that both l1--a-->l2 in L and r1--a-->r2 in R.
The maximal number of states of B is the product of the number of states of L and R but almost all this states are non reachable from the initial state (1,1).
The algorithm used in function 'sync_product()
' builds
the minimal product DFA only by keeping the reachable states.
It recursively scans the product CDFA by following simultaneously
the transitions of L and R. A hast table
(gtest
) is used to check if a state (l,r) has
already been reached, the reachable states are remapped on
a new DFA. The CDFA thus obtained is minimal and recognizes the
union of the two patterns sets.
For example these two CDFA's:
Give by synchronization product the following one:
It is possible to construct a special pattern database that generates an "explosive" automaton: the size of the DFA is in the worst case exponential in the number of patterns it recognizes. But it doesn't occur in pratical situations: the dfa size tends to be stable. By stable we mean that if we add a pattern which greatly increases the size of the dfa it also increases the chance that the next added pattern does not increase its size at all. Nevertheless there are many ways to reduce the size of the DFA. Good compression methods are explained in Aho, Ravi Sethi, Ullman "COMPILERS: Principles, Techniques and Tools" chapter Optimization of DFA-based pattern matchers.
The incremental version of the DFA pattern matcher is not yet implemented in gnugo but we explain here how it will work. By definition of a deterministic automaton, scanning the same string will reach the same states every time.
Each reached state during pattern matching is stored in a stack
top_stack[i][j]
and state_stack[i][j][stack_idx]
We use one stack by intersection (i,j)
. A precomputed reverse
path list allows to know for each couple of board intersections
(x,y)
its position reverse(x,y)
in the spiral scan path
starting from (0,0)
.
When a new stone is put on the board at (lx,ly)
, the only work
of the pattern matcher is:
for(each stone on the board at (i,j))
if(reverse(lx-i,ly-j) < top_stack[i][j])
{
begin the dfa scan from the state
state_stack[i][j][reverse(lx-i,ly-j)];
}
In most situations reverse(lx-i,ly-j) will be inferior to top_stack[i][j]. This should speedup a lot pattern matching.
The dfa is constructed to minimize jumps in memory making some assumptions about the frequencies of the values: the EMPTY value is supposed to appear often on the board, so the the '.' transition are almost always successors in memory. The OUT_BOARD are supposed to be rare, so '#' transitions will almost always imply a big jump.
The process of visualizing potential moves done by you and your
opponent to learn the result of different moves is called
"reading". GNU Go does three distinct types of reading: tactical
reading which typically is concerned with the life and death of
individual strings, Owl reading which is concerned
with the life and death of dragons, and life reading
which attempts evaluate eye spaces. In this Chapter, we document
the tactical reading code, which is in engine/reading.c
.
For a summary of the reading functions see See Reading Functions.
engine/reading.c
In GNU Go, tactical reading is done by the functions in
engine/reading.c
. Each of these functions has a separate goal to fill,
and they call each other recursively to carry out the reading process.
The reading code makes use of a stack onto which board positions can
be pushed. The parameter stackp
is zero if GNU Go is
examining the true board position; if it is higher than zero, then
GNU Go is examining a hypothetical position obtained by playing
several moves.
The most important public reading functions are attack
and
find_defense
. These are wrappers for functions do_attack
and
do_find_defense
which are declared statically in reading.c
. The
functions do_attack
and do_find_defense
call each other
recursively.
The return codes of the reading (and owl) functions and owl can be 0, 1, 2 or 3. Each reading function determines whether a particular player (assumed to have the move) can solve a specific problem, typically attacking or defending a string.
The nonzero return codes are called these names in the source:
#define WIN 3 #define KO_A 2 #define KO_B 1
A return code of WIN means success, 0 failure, while KO_A and KO_B are success conditioned on ko. A function returns KO_A if the position results in ko and that the player to move will get the first ko capture (so the opponent has to make the first ko threat). A return code of KO_B means that the player to move will have to make the first ko threat.
Many of the reading functions make use of null pointers.
For example, a call to attack(i, j, &ai, &aj)
will return
WIN if the string at (i, j)
can be captured. The point of
attack (in case it is vulnerable) is returned in
(ai, aj)
. However many times we do not care about the
point of attack. In this case, we can substitute a null pointer:
attack(i, j, NULL, NULL)
.
Depth of reading is controlled by the parameters depth
and
branch_depth
. The depth
has a default value DEPTH
(in
liberty.h
), which is set to 14 in the distribution, but it may also be
set at the command line using the -D
or --depth
option.
If depth
is increased, GNU Go will be stronger and slower. GNU Go will
read moves past depth, but in doing so it makes simplifying assumptions that
can cause it to miss moves.
Specifically, when stackp > depth
, GNU Go assumes that as soon
as the string can get 3 liberties it is alive. This assumption is
sufficient for reading ladders.
The branch_depth
is typically set a little below depth
.
Between branch_depth
and depth
, attacks on strings with
3 liberties are considered, but branching is inhibited, so fewer
variations are considered.
Currently the reading code does not try to defend a string by
attacking a boundary string with more than two liberties. Because
of this restriction, it can make oversights. A symptom of this is
two adjacent strings, each having three or four liberties, each
classified as DEAD
. To resolve such situations, a function
small_semeai()
(in engine/semeai.c
) looks for such
pairs of strings and corrects their classification.
The backfill_depth is a similar variable with a default 10. Below this depth, GNU Go will try "backfilling" to capture stones. For example in this situation:
.OOOOOO. on the edge of the board, O can capture X but OOXXXXXO in order to do so he has to first play at a in .aObX.XO preparation for making the atari at b. This is -------- called backfilling.
Backfilling is only tried with stackp <= backfill_depth
. The
parameter backfill_depth
may be set using the -B
option.
The fourlib_depth
is a parameter with a default of only 5.
Below this depth, GNU Go will try to attack strings with
four liberties. The fourlib_depth
may be set using the
-F
option.
The parameter ko_depth
is a similar cutoff. If
stackp<ko_depth
, the reading code will make experiments
involving taking a ko even if it is not legal to do so (i.e., it
is hypothesized that a remote ko threat is made and answered
before continuation). This parameter may be set using the
-K
option.
A partial list of the functions in reading.c
:
int attack(int m, int n, int *i, int *j)
:
The basic functionattack(m, n, *i, *j)
determines if the string at(m, n)
can be attacked, and if so,(*i, *j)
returns the attacking move, unless*i
and*j
are null pointers. (Use null pointers if you are interested in the result of the attack but not the attacking move itself.) Returns 1 if the attack succeeds, otherwise 0. Returns KO_A or KO_B if the result depends on ko: returns KO_A if the attack succeeds provided attacker is willing to ignore any ko threat. Returns KO_B if attack succeeds provided attacker has a ko threat which must be answered.
find_defense(int m, int n, int *i, int *j)
:
The functionfind_defense(m, n, *i, *j)
attempts to find a move that will save the string at(m,n)
. It returns true if such a move is found, with(*i, *j)
the location of the saving move (unless(*i, *j)
are null pointers). It is not checked that tenuki defends, so this may give an erroneous answer if!attack(m,n)
. Returns KO_A or KO_B if the result depends on ko. Returns KO_A if the string can be defended provided (color) is willing to ignore any ko threat. Returns KO_B if (color) has a ko threat which must be answered.
safe_move(int i, int j, int color)
:
The functionsafe_move(i, j, color)
checks whether a move at(i, j)
is illegal or can immediately be captured. Ifstackp==0
the result is cached. If the move only can be captured by a ko, it's considered safe. This may or may not be a good convention.
The next few functions are essentially special cases of attack
and find_defense
. They are coded individually, and are
static in engine/reading.c
.
attack2(int m, int n, int *i, int *j)
:
Determine whether a string with 2 liberties can
be captured. Usage is similar to attack
.
attack3(int m, int n, int *i, int *j)
:
Determine whether a string with 3 liberties can
be captured. Usage is similar to attack
.
attack4(int m, int n, int *i, int *j)
:
Determine whether a string with 4 liberties can
be captured. Usage is similar to attack
.
defend1(int m, int n, int *i, int *j)
:
Determine whether a string with 1 liberty can be
rescued. Usage is similar to find_defense
.
defend2()
:
Determine whether a string with 2 liberties can be
rescued. Usage is similar to find_defense
.
defend3()
:
Determine whether a string with 3 liberties can be
rescued. Usage is similar to find_defense
.
find_cap2()
:
If(m,n)
points to a string with 2 liberties,find_cap2(m,n,&i,&j)
looks for a configuration:O. .*where
O
is an element of the string in question. It tries the move at*
and returns true this move captures the string, leaving(i,j)
pointing to *.
break_chain(int si, int sj, int *i, int *j, int *k, int *l)
:
The functionbreak_chain(si, sj, *i, *j, *k, *l)
returns 1 if part of some surrounding string is in atari, and if capturing this string results in a live string at(si, sj)
. Returns 2 if the capturing string can be taken (as in a snapback), or the the saving move depends on ignoring a ko threat; Returns 3 if the saving move requires making a ko threat and winning the ko. The pointers(i,j)
, if not NULL, are left pointing to the appropriate defensive move. The pointers(k,l)
, if not NULL, are left pointing to the boundary string which is in atari.
break_chain2(int si, int sj, int *i, int *j)
:
The functionbreak_chain2(si, sj, *i, *j)
returns 1 if there is a string in the surrounding chain having exactly two liberties whose attack leads to the rescue of(si, sj)
. Then*i, *j
points to the location of the attacking move. Returns 2 if the attacking stone can be captured, 1 if it cannot.
snapback(snapback(int si, int sj, int i, int j, int color)
:
The functionsnapback(si, sj, i, j, color)
considers a move by color at(i, j)
and returns true if the move is a snapback. Algorithm: It removes dead pieces of the other color, then returns 1 if the stone at(si, sj)
has <2 liberties. The purpose of this test is to avoid snapbacks. The locations(i, j)
and(si,sj)
may be either same or different. Also returns 1 if the move at(i, j)
is illegal, with the trace message "ko violation" which is the only way I think this could happen. It is not a snapback if the capturing stone can be recaptured on its own, e.g.XXOOOOO X*XXXXO -------Here
O
capturing at*
is in atari, but this is not a snapback. Use with caution: you may want to condition the test on the string being captured not being a singleton. For exampleXXXOOOOOOOO XO*XXXXXXXO -----------is rejected as a snapback, yetO
captures more than it gives up.
To speed up the reading process, we note that a position can be reached in several different ways. In fact, it is a very common occurrence that a previously checked position is rechecked, often within the same search but from a different branch in the recursion tree.
This wastes a lot of computing resources, so in a number of places, we store away the current position, the function we are in, and which worm is under attack or to be defended. When the search for this position is finished, we also store away the result of the search and which move made the attack or defense succeed.
All this data is stored in a hash table, sometimes also called a
transposition table, where Go positions are the key and results of the
reading for certain functions and groups are the data. You can increase
the size of the Hash table using the -M
or --memory
option see Invoking GNU Go.
The hash table is created once and for all at the beginning of
the game by the function hashtable_new()
. Although hash
memory is thus allocated only once in the game, the table is
reinitialized at the beginning of each move by a call to
hashtable_clear()
from genmove()
.
hash.h
The hash algorithm is called Zobrist hashing, and is a standard technique for go and chess programming. The algorithm as used by us works as follows:
It is not necessary to specify the color to move (white or black)
as part of the position. The reason for this is that read results
are stored separately for the various reading functions such as
attack3
, and it is implicit in the calling function which
player is to move.
These random numbers are generated once at initialization time and then used throughout the life time of the hash table.
The hash table consists of 3 parts:
Each Read Result contains:
When the hash table is created, these 3 areas are allocated using
malloc()
. When the hash table is populated, all contents are taken
from the Hash nodes and the Read results. No further allocation is
done and when all nodes or results are used, the hash table is full.
Nothing is deleted from the hash table except when it is totally
emptied, at which point it can be used again as if newly initialized.
When a function wants to use the hash table, it looks up the current
position using hashtable_search()
. If the position doesn't already
exist there, it can be entered using
hashtable_enter_position()
.
Once the function has a pointer to the hash node containing a
function, it can search for a result of a previous search using
hashnode_search()
. If a result is found, it can be used, and
if not, a new result can be entered after a search using
hashnode_new_result()
.
Hash nodes which hash to the same position in the hash table (collisions) form a simple linked list. Read results for the same position, created by different functions and different attacked or defended strings also form a linked list.
This is deemed sufficiently efficient for now, but the representation of collisions could be changed in the future. It is also not determined what the optimum sizes for the hash table, the number of positions and the number of results are.
The basic hash structures are declared in hash.h
.
typedef struct hashposition_t { Compacttype board[COMPACT_BOARD_SIZE]; int ko_i; int ko_j; } Hashposition;
Represents the board and optionally the location of a ko, which is an illegal move. The player whose move is next is not recorded.
typedef struct { Hashvalue hashval; Hashposition hashpos; } Hash_data;
Represents the return value of a function (hashval
) and
the board state (hashpos
).
typedef struct read_result_t { unsigned int compressed_data; int result_ri_rj; struct read_result_t *next; } Read_result;
Here the compressed_data
field packs into 32 bits the
following fields:
komaster: 2 bits (EMPTY, BLACK, WHITE, or GRAY) kom_i : 5 bits kom_j : 5 bits routine : 4 bits (currently 10 different choices) i : 5 bits j : 5 bits stackp : 5 bits
The komaster
and (kom_i,kom_j)
field are
documented in See Ko. The integer result_ri_rj
encodes:
unsigned char status; unsigned char result; unsigned char ri; unsigned char rj;
When a new result node is created, 'status' is set to 1 'open'. This is then set to 2 'closed' when the result is entered. The main use for this is to identify open result nodes when the hashtable is partially cleared. Another potential use for this field is to identify repeated positions in the reading, in particular local double or triple kos.
typedef struct hashnode_t { Hash_data key; Read_result * results; struct hashnode_t * next; } Hashnode;
The hash table consists of hash nodes. Each hash node consists of The hash value for the position it holds, the position itself and the actual information which is purpose of the table from the start.
There is also a pointer to another hash node which is used when the nodes are sorted into hash buckets (see below).
typedef struct hashtable { size_t hashtablesize; /* Number of hash buckets */ Hashnode ** hashtable; /* Pointer to array of hashnode lists */ int num_nodes; /* Total number of hash nodes */ Hashnode * all_nodes; /* Pointer to all allocated hash nodes. */ int free_node; /* Index to next free node. */ int num_results; /* Total number of results */ Read_result * all_results; /* Pointer to all allocated results. */ int free_result; /* Index to next free result. */ } Hashtable;
The hash table consists of three parts:
The following functions are defined in hash.c
:
void hash_init()
Initialize the entire hash system.
int hashdata_compare(Hash_data *key1, Hash_data *key2)
Returns 0 if *key1 == *key2
, 2 if the hashvalues differ, or 1 if
only the hashpositions differ.
This adheres (almost) to the standard compare function semantics
which are used e.g. by the comparison functions used in qsort().
void hashposition_dump(Hashposition *pos, FILE *outfile)
Dump an ASCII representation of the contents of a Hashposition onto the FILE outfile.
int hashdata_diff_dump(Hash_data *key1,Hash_data *key2 )
Compare two Hashdata structs. If equal: return zero. If not: dump a human readable summary of any differences to stderr. The return value is the same as for hashdata_compare. This function is primarily intended to be used in assert statements.
void hashdata_recalc(Hash_data *target, Intersection board[MAX_BOARD][MAX_BOARD], int koi, int koj)
Calculate the compactboard and the hashvalue in one function. They are always used together and it saves us a loop and a function call.
void hashdata_set_ko(Hash_data *hd, int i, int j)
Set or remove a ko at (i, j).
void hashdata_remove_ko(Hash_data *hd)
Remove any ko from the hash value and hash position.
void hashdata_invert_stone(Hash_data *hd, int i, int j, int color)
Set or remove a stone of COLOR at (I, J) in a Hash_data.
void read_result_dump(Read_result *result, FILE *outfile)
Dump an ASCII representation of the contents of a Read_result onto the FILE outfile.
void hashnode_dump(Hashnode *node, FILE *outfile)
Dump an ASCII representation of the contents of a Hashnode onto the FILE outfile.
int hashtable_init(Hashtable *table, int tablesize, int num_nodes, int num_results)
Initialize a hash table for a given total size and size of the hash table. Returns 0 if something went wrong. Just now this means that there wasn't enough memory available.
Hashtable * hashtable_new(int tablesize, int num_nodes, int num_results)
Allocate a new hash table and return a pointer to it. Return NULL if there is insufficient memory.
void hashtable_clear(Hashtable *table)
Clear an existing hash table.
void hashtable_clear_if_full(Hashtable *table)
Clear an existing hash table only if it happens to be full. By full we mean that we are either out of positions or read results.
Hashnode * hashtable_enter_position(Hashtable *table, Hash_data *hd)
Enter a position with a given hash value into the table. Return a pointer to the hash node where it was stored. If it is already there, don't enter it again, but return a pointer to the old one.
Hashnode * hashtable_search(Hashtable *table, Hash_data *hd)
Given a Hashposition and a Hash value, find the hashnode which contains this position with the given hash value.
void hashtable_dump(Hashtable *table, FILE *outfile)
Dump an ASCII representation of the contents of a Hashtable onto the FILE outfile.
Read_result * hashnode_search(Hashnode *node, int routine, int i, int j)
Search the result list in a hash node for a particular result. This result is fromroutine
(the calling function) at(i, j)
and reading depth stackp. All these numbers must be unsigned, and 0<= x <= 255).
Read_result * hashnode_new_result(Hashtable *table, Hashnode *node, int routine, int i, int j)
Enter a new Read_result into a Hashnode. We already have the node, now we just want to enter the result itself. We will fill in the result itself later, so we only need the routine number for now.
The following macros are defined in hash.h
rr_get_routine(Read_result rr)
rr_get_pos_i(Read_result rr)
rr_get_pos_j(Read_result rr)
rr_get_stackp(Read_result rr)
Get the constituent parts of a Read_result
.
The following macros and functions are defined in
engine/reading.c
:
static int get_read_result(int routine, int *si, int *sj, Read_result **read_result)
Return a Read_result for the current position, routine and location. For performance, the location is changed to the origin of the string.
READ_RETURN0(Read_result *read_result)
Cache a negative read result.
READ_RETURN(Read_result *read_result, int *pointi, int *pointj, int resulti, int resultj, int value)
Ifpointi
andpointj
are not null pointers, then give(*pointi, *pointj)
the values(resulti, resultj)
. Then cache theread_result
. Clear the hashtable if full and returnvalue
.
Some reading calculations can be safely saved from move to move.
The function store_persistent_cache()
is called only
by attack
and find_defense
, never from their
static recursive counterparts do_attack
and do_defend
.
The function store_persistent_reading_cache()
attempts to
cache the most expensive reading results. The function
search_persistent_reading_cache
attempts to retrieve a
result from the cache.
If all cache entries are occupied, we try to replace the least useful one. This is indicated by the score field, which is initially the number of nodes expended by this particular reading, and later multiplied by the number of times it has been retrieved from the cache.
Once a (permanent) move is made, a number of cache entries immediately become
invalid. These are cleaned away by the function
purge_persistent_reading_cache().
To have a criterion
for when a result may be purged, the function
store_persistent_cache()
computes the
reading shadow and active area. If a permanent
move is subsequently played in the active area, the cached
result is invalidated. We now explain this algorithm in detail.
The reading shadow is the concatenation of all moves in all variations, as well as locations where an illegal move has been tried.
Once the read is finished, the reading shadow is expanded to the active area which may be cached. The intention is that as long as no stones are played in the active area, the cached value may safely be used.
Here is the algorithm used to compute the active area.
This algorithm is in the function store_persistent_reading_cache()
.
The most expensive readings so far are stored in the persistent cache.
1
. We also include the successful
move, which is most often a part of the reading shadow, but
sometimes not, for example with the function attack1()
.
1
with
the character 2
.
2
are
labelled with the character 3
.
-1
instead of the more logical 4
because it
is slightly faster to code this way.
The principles of ko handling are the same for tactical reading and owl reading.
We have already mentioned (see Reading Basics) that GNU Go uses a return code of KO_A or KO_B if the result depends on ko. The return code of KO_B means that the position can be won provided the player whose move calls the function can come up with a sufficiently large ko threat. In order to verify this, the function must simulate making a ko threat and having it answered by taking the ko even if it is illegal. We call such an experimental taking of the ko a conditional ko capture.
Conditional ko captures are accomplished by the function tryko()
.
This function is like trymove()
except that
it does not require legality of the move in question.
The static reading functions, and the global functions do_attack
and do_find_defense
have arguments komaster
, kom_i
and kom_j
. These mediate ko captures to prevent the occurrence of
infinite loops.
Normally komaster
is EMPTY but it can also be BLACK, WHITE or
GRAY. The komaster is set to COLOR when COLOR makes a conditional ko
capture. In this case kom_i, kom_j
is set to the location of the
captured ko stone.
If the opponent is komaster, the reading functions will not try to
take the ko at kom_i, kom_j
. Also, the komaster is normally not
allowed to take another ko. The exception is a nested ko, characterized
by the condition that the captured ko stone is at distance 1 both
vertically and horizontally from (kom_i, kom_j)
, which is the location
of the last stone taken by the komaster. Thus in this situation:
.OX OX*X OmOX OO
Here if m
is the location of (kom_i,kom_j)
, then the move at
*
is allowed.
The rationale behind this rule is that in the case where there are two kos on the board, the komaster cannot win both, and by becoming komaster he has already chosen which ko he wants to win. But in the case of a nested ko, taking one ko is a precondition to taking the other one, so we allow this.
If the komaster's opponent takes a ko, then both players have taken one ko. In this case `komaster' is set to GRAY and after this further ko captures are not allowed.
If the ko at (kom_i, kom_j)
is filled, then the komaster
reverts to EMPTY.
The komaster scheme may be summarized as follows. It is assumed
that O
is about to move.
O
and
(kom_i, kom_j)
to the location of the ko, where a stone was
just removed.
(kom_i,kom_j)
then komaster reverts to
EMPTY.
(kom_i,kom_j)
is not allowed. Any other ko capture
is allowed. If O
takes another ko, komaster becomes GRAY.
(kom_i,kom_j)
is
filled then the komaster reverts to EMPTY.
To see the komaster scheme in action, consider this position
from the file regressions/games/life_and_death/tripod9.sgf
.
We recommend studying this example by examining the variation file
produced by the command:
gnugo -l tripod9.sgf --decidedragon C3 -o vars.sgf
In the lower left hand corner, there are kos at A2 and B4. Black is unconditionally dead because if W wins either ko there is nothing B can do.
8 . . . . . . . . 7 . . O . . . . . 6 . . O . . . . . 5 O O O . . . . . 4 O . O O . . . . 3 X O X O O O O . 2 . X X X O . . . 1 X O . . . . . . A B C D E F G H
This is how the komaster scheme sees this. B (i.e. X) starts by taking the ko at B4. W replies by taking the ko at A1. The board looks like this:
8 . . . . . . . . 7 . . O . . . . . 6 . . O . . . . . 5 O O O . . . . . 4 O X O O . . . . 3 X . X O O O O . 2 O X X X O . . . 1 . O . . . . . . A B C D E F G H
Now any move except the ko recapture (currently illegal) at A1 loses for B, so B retakes the ko and becomes komaster. The board looks like this:
8 . . . . . . . . komaster: BLACK 7 . . O . . . . . (kom_i, kom_j): A2 6 . . O . . . . . 5 O O O . . . . . 4 O X O O . . . . 3 X . X O O O O . 2 . X X X O . . . 1 X O . . . . . . A B C D E F G H
W takes the ko at B3 after which the komaster is GRAY and ko recaptures are not allowed.
8 . . . . . . . . komaster: GRAY 7 . . O . . . . . (kom_i, kom_j): B4 6 . . O . . . . . 5 O O O . . . . . 4 O . O O . . . . 3 X O X O O O O . 2 . X X X O . . . 1 X O . . . . . . A B C D E F G H
Since X is not allowed any ko recaptures, there is nothing he can do and he is found dead. Thus the komaster scheme produces the correct result.
We now consider an example to show why the komaster is reset to EMPTY if the ko is resolved in the komaster's favor. This means that the ko is filled, or else that is becomes no longer a ko and it is illegal for the komaster's opponent to play there.
The position resulting under consideration is in the file
regressions/games/ko5.sgf
. This is the position:
. . . . . . O O 8 X X X . . . O . 7 X . X X . . O . 6 . X . X X X O O 5 X X . X . X O X 4 . O X O O O X . 3 O O X O . O X X 2 . O . X O X X . 1 F G H J K L M N
We recommend studying this example by examining the variation file produced by the command:
gnugo -l ko5.sgf --quiet --decidestring L1 -o vars.sgf
The correct resolution is that H1 attacks L1 while K2 defends it with ko (code KO_A).
After Black (X) takes the ko at K3, white can do nothing but retake the ko conditionally, becoming komaster. B cannot do much, but in one variation he plays at K4 and W takes at H1. The following position results:
. . . . . . O O 8 X X X . . . O . 7 X . X X . . O . 6 . X . X X X O O 5 X X . X X X O X 4 . O X O O O X . 3 O O X O . O X X 2 . O O . O X X . 1 F G H J K L M N
Now it is important the O
is no longer komaster. Were O
still komaster, he could capture the ko at N3 and there would be
no way to finish off B.
The following alternate schemes have been proposed. It is assumed
that O
is the player about to move.
(kom_i, kom_j)
to the location of the ko, where a stone was
just removed.
(kom_i, kom_j)
. Komaster parameters unchanged.
O
and
(kom_i, kom_j)
to the location of the ko, where a stone was
just removed.
O
:
is_ko(kom_i, kom_j, X)
returns false. In that case,
(kom_i, kom_j)
is updated to the new ko position, i.e. the stone
captured by this move.
(kom_i, kom_j)
. Komaster parameters unchanged.
A superstring is an extended string, where the extensions are through the following kinds of connections:
OO
... O.O XOX X.X
OO .. OO
.O O.
reading.c
, but included when the superstring code is
called from owl.c
.
Like a dragon, a superstring is an amalgamation of strings, but it is a much tighter organization of stones than a dragon, and its purpose is different. Superstrings are encountered already in the tactical reading because sometimes attacking or defending an element of the superstring is the best way to attack or defend a string. This is in contrast with dragons, which are ignored during tactical reading.
Here we list the publically callable functions in reading.c
.
The return codes of these functions are explained elsewhere
(see Reading Basics).
attack(si, sj, *i, *j)
Determines if the string at (m, n) can be captured, and if so, (*i, *j) returns the attacking move, unless (*i, *j) are null pointers. Use null pointers if you are interested in the result of the attack but not the attacking move itself. The string is assumed to be alive if it can get five liberties--fewer ifstackp
is large.
- Returns 1 if the attack succeeds unconditionally
- Returns 0 if the attack fails unconditionally
- Returns 2 if the attack succeeds provided attacker is willing to ignore any ko threat (the attacker makes the first ko capture).
- Returns 3 if attack succeeds provided attacker has a ko threat which must be answered (the defender makes the first ko capture).
find_defense(m, n, *i, *j)
Attempts to find a move that will save the string at(m, n)
. It returns 1 if such a move is found, with(*i, *j)
the location of the saving move, unless(*i, *j)
are null pointers. It is not checked that tenuki defends, so this may give an erroneous answer if!attack(m,n)
. Returns 2 or 3 if the result depends on ko. Returns 2 if the string can be defended provided the defender is willing to ignore any ko threat. Returns 3 if the defender wins by having a ko threat which must be answered.
int attack_and_defend(int si, int sj, int *attack_code, int *attacki, int *attackj,int *defend_code, int *defendi, int *defendj)
This is a frontend to theattack()
andfind_defense()
which guarantees a consistent result. If a string cannot be attacked, 0 is returned and acode is 0. If a string can be attacked and defended, WIN is returned, acode and dcode are both non-zero, and(ai, aj)
,(di, dj)
both point to vertices on the board. If a string can be attacked but not defended, 0 is again returned, acode is non-zero, dcode is 0, and (ai, aj) point to a vertex on the board. This function in particular guarantees that if there is an attack, it will never return(di, dj) = (-1, -1)
, which means the string is safe without defense. Separate calls toattack()
andfind_defense()
may occasionally give this result, due to irregularities introduced by the persistent reading cache.
attack_either(ai, aj, bi, bj)
returns true if there is a move which guarantees that at least one of the strings(ai, aj)
and(bi, bj)
can be captured. A typical application for this is in connection patterns, where after a cut it suffices to capture one of the cutting stones. The current implementation looks only for uncoordinated attacks and is not even sufficient to find a double atari.
defend_both(ai, aj, bi, bj)
Returns true if both the strings(ai, aj)
and(bi, bj)
can be defended simultaneously or if there is no attack. A typical application for this is in connection patterns, where after a cut it's necessary to defend both cutting stones.
int break_through(int ai, int aj, int bi, int bj, int ci, int cj)
Returns 1 if a position can succesfully be broken through and 2 if it can be cut. The position is assumed to have the shape (the colors may be reversed).O. dbe OXO aFcIt isX
to move and try to capture at least one ofa
,b
, andc
. If this succeeds,X
is said to have broken through the position. OtherwiseX
may try to cut through the position, which means keepingF
safe and getting a tactically safe string at eitherd
ore
. Important:a
,b
, andc
must be given in the correct order.
int atari_atari(int color, int *i, int *j, int save_verbose)
Looks for a series of ataris on strings of the other color culminating in the capture of a string which is thought to be invulnerable by the reading code. Such a move can be missed since it may be that each string involved individually can be rescued, but nevertheless one of them can be caught. The simplest example is a double atari. The return value is the size of the smallest opponent worm. A danger with this scheme is that the first atari tried might be irrelevant to the actual combination. To avoid this, once we've found a combination, we mark the first move as forbidden, then try again. If no combination of the same size or larger turns up, then the first move was indeed essential. Returns the size of the smallest of the worms under attack.
int atari_atari_confirm_safety(int color, int ti, int tj, int *i, int *j, int minsize)
Uses theatari_atari
code to detect blunders. Ask whether there appears any combination attack which would capture at least minsize stones after playing at(ti, tj)
. If this happens,(*i, *j)
points to a defensive move which prevents this blunder.
int atari_atari_try_combination(int color, int ai, int aj, int bi, int bj)
Ask the atari_atari code if after color plays at (ai,aj) and other plays at (bi,bj) there appears any combination attack. Returns the size of the combination.
The reading code searches for a path through the move tree to
determine whether a string can be captured. We have a tool for
investigating this with the --decidestring
option. This may
be run with or without an output file.
Simply running
gnugo -t -l [input file name] -L [movenumber] --decidestring [location]
will run attack()
to determine whether the string can be captured.
If it can, it will also run find_defense()
to determine whether or
not it can be defended. It will give a count of the number of
variations read. The -t
is necessary, or else GNU Go will not
report its findings.
If we add -o output file
GNU Go will produce
an output file with all variations considered. The variations are
numbered in comments.
This file of variations is not very useful without a way of navigating the source code. This is provided with the GDB source file, listed at the end. You can source this from GDB, or just make it your GDB init file.
If you are using GDB to debug GNU Go you may find it less
confusing to compile without optimization. The optimization
sometimes changes the order in which program steps are
executed. For example, to compile reading.c
without optimization,
edit engine/Makefile
to remove the string -O2
from
the file, touch engine/reading.c
and make. Note that the
Makefile is automatically generated and may get overwritten
later.
If in the course of reading you need to analyze a result where
a function gets its value by returning a cached position from
the hashing code, rerun the example with the hashing turned off
by the command line option --hash 0
. You should get the same
result. (If you do not, please send us a bug report.) Don't
run --hash 0
unless you have a good reason to, since it
increases the number of variations.
With the source file given at the end of this document loaded,
we can now navigate the variations. It is a good idea to use
cgoban with a small -fontHeight
, so that the
variation window takes in a big picture. (You can resize the
board.)
Suppose after perusing this file, we find that variation 17 is interesting and we would like to find out exactly what is going on here.
The macro 'jt n' will jump to the n-th variation.
(gdb) set args -l [filename] -L [move number] --decidestring [location] (gdb) tbreak main (gdb) run (gdb) jt 17
will then jump to the location in question.
Actually the attack variations and defense variations are numbered
separately. (But find_defense()
is only run if attack()
succeeds,
so the defense variations may or may not exist.) It is redundant to
have to tbreak main each time. So there are two macros avar and dvar.
(gdb) avar 17
restarts the program, and jumps to the 17-th attack variation.
(gdb) dvar 17
jumps to the 17-th defense variation. Both variation sets are found in the same sgf file, though they are numbered separately.
Other commands defined in this file:
dump
will print the move stack.nv
moves to the next variationascii i j
converts (i,j) to ascii ####################################################### ############### .gdbinit file ############### ####################################################### # this command displays the stack define dump set dump_stack() end # display the name of the move in ascii define ascii set gprintf("%o%m\n",$arg0,$arg1) end # display the all information about a dragon define dragon set ascii_report_dragon("$arg0") end define worm set ascii_report_worm("$arg0") end # move to the next variation define nv tbreak trymove continue finish next end # move forward to a particular variation define jt while (count_variations < $arg0) nv end nv dump end # restart, jump to a particular attack variation define avar delete tbreak sgffile_decidestring run tbreak attack continue jt $arg0 end # restart, jump to a particular defense variation define dvar delete tbreak sgffile_decidestring run tbreak attack continue finish next 3 jt $arg0 end
GNU Go does two very different types of life and death reading. First,
there is the OWL code (Optics with Limit Negotiation) which
attempts to read out to a point where the code in
engine/optics.c
(see Eyes) can be used to evaluate it.
Secondly, there is the code in engine/life.c
which
is a potential replacement for the code in optics.c
.
It attempts to evaluate eyespaces more accurately than the
code in optics.c
, but since it is fairly slow,
it is partially disabled unless you run GNU Go with the
option --life
. The default use of the life code
is that it can be called from optics.c
when the graph
based life and death code concludes that it needs an expert
opinion.
Like the tactical reading code, a persistent cache is employed to maintain some of the owl data from move to move. This is an essential speedup without which GNU Go would play too slowly.
owl.c
The life and death code in optics.c
, described elsewhere
(see Eyes), works reasonably well as long as the position is in a
terminal position, which we define to be one where there are no
moves left which can expand the eye space, or limit it. In situations
where the dragon is surrounded, yet has room to thrash around a bit
making eyes, a simple application of the graph-based analysis will not
work. Instead, a bit of reading is needed to reach a terminal position.
The defender tries to expand his eyespace, the attacker to limit
it, and when neither finds an effective move, the position is
evaluated. We call this type of life and death reading
Optics With Limit-negotiation (OWL). The module which
implements it is in engine/owl.c
.
There are two reasonably small databases
patterns/owl_defendpats.db
and patterns/owl_attackpats.db
of expanding and limiting moves. The code in owl.c
generates a
small move tree, allowing the attacker only moves from
owl_attackpats.db
, and the defender only moves from
owl_defendpats.db
. In addition to the moves suggested by
patterns, vital moves from the eye space analysis are also tested.
A third database, owl_vital_apats.db
includes patterns which
override the eyespace analysis done by the optics code. Since the
eyeshape graphs ignore the complications of shortage of liberties and
cutting points in the surrounding chains, the static analysis of
eyespace is sometimes wrong. The problem is when the optics code says
that a dragon definitely has 2 eyes, but it isn't true due to
shortage of liberties, so the ordinary owl patterns never get into play.
In such situations owl_vital_apats.db
is the only available measure
to correct mistakes by the optics. Currently the patterns in
owl_vital_apats.db
are only matched when the level is 9 or
greater.
The owl code is tuned by editing these three pattern databases, principally the first two.
A node of the move tree is considered terminal
if no further moves
are found from apats.db
or dpats.db
, or if the function
compute_eyes_pessimistic()
reports that the group is definitely
alive or dead. At this point, the status of the group is evaluated.
The functions owl_attack()
and owl_defend()
, with
usage similar to attack()
and find_defense()
, make
use of the owl pattern databases to generate the move tree and decide
the status of the group.
The function compute_eyes_pessimistic()
used by the owl
code is very conservative and only feels certain about eyes if the
eyespace is completely closed (i.e. no marginal vertices).
The maximum number of moves tried at each node is limited by
the parameter MAX_MOVES
defined at the beginning of
engine/owl.c
. The most most valuable moves are
tried first, with the following restrictions:
stackp > owl_branch_depth
then only one move is tried per
variation.
stackp > owl_reading_depth
then the reading terminates,
and the situation is declared a win for the defender (since
deep reading may be a sign of escape).
owl_node_limit
, the reading also
terminates with a win for the defender.
patterns/owl_attackpats.db
and
patterns/owl_defendpats.db
with value 100 is considered a win: if
such a pattern is found by owl_attack
or owl_defend
, the
function returns true. This feature must be used most carefully.
The functions owl_attack()
and owl_defend()
may, like
attack()
and find_defense()
, return an attacking or
defending move through their pointer arguments. If the position is
already won, owl_attack()
may or may not return an attacking
move. If it finds no move of interest, it will return PASS
, that
is, (-1,-1)
. The same goes for owl_defend()
.
When owl_attack()
or owl_defend()
is called,
the dragon under attack is marked in the array goal
.
The stones of the dragon originally on the board are marked
with goal=1; those added by owl_defend()
are marked
with goal=2. If all the original strings of the original dragon
are captured, owl_attack()
considers the dragon to be defeated,
even if some stones added later can make a live group.
Only dragons with small escape route are studied when the
functions are called from make_dragons()
.
The owl code can be conveniently tested using the
--decidedragon location
This should be used with
-t
to produce a useful trace, -o
to produce
an SGF file of variations produced when the life and death of
the dragon at location is checked, or both.
--decideposition
performs the same analysis for all
dragons with small escape route.
owl.c
In this section we list the non-static functions in owl.c
.
Note that calls to owl_attack
and owl_defend
should
be made only when stackp==0
. If you want to set up a
position, then use the owl code to analyze it, you may call
do_owl_attack
and do_owl_defend
with stackp>0
but first you must set up the goal and boundary arrays. See
owl_does_defend
and owl_substantial
for examples.
The reason that we do not try to write a general owl_attack
which works when stackp>0
is that we make use of cached
information in the calls to same_dragon
from the (static)
function owl_mark_dragon
. This requires the dragon data
to be current, which it is not when stackp>0
.
int owl_attack(int m, int n, int *ui, int *uj)
Returns 1 if a move can be found to attack the dragon at(m, n)
, in which case(*ui, *uj)
is the recommended move.(*ui, *uj)
can be null pointers if the result is not needed.
- Returns 2 if the attack prevails provided attacker is willing to ignore any ko threat (the attacker makes the first ko capture).
- Returns 3 if attack succeeds provided attacker has a ko threat which must be answered (the defender makes the first ko capture).
int owl_threaten_attack(int m, int n, int *ui, int *uj, int *vi, int *vj)
Returns 1 if the dragon at(m, n)
can be captured given two moves in a row. The first two moves to capture the dragon are given as(*ui, *uj)
and(*vi, *vj)
.
int owl_defend(int m, int n, int *ui, int *uj)
Returns 1 if a move can be found to defend the dragon at(m, n)
, in which case(*ui, *uj)
is the recommended move.(*ui, *uj)
can be null pointers if the result is not needed.
- Returns 2 if the defense prevails provided defender is willing to ignore any ko threat (the defender makes the first ko capture).
- Returns 3 if defense succeeds provided defender has a ko threat which must be answered (the attacker makes the first ko capture).
int owl_threaten_defense(int m, int n, int *ui, int *uj, int *vi, int *vj)
Returns true if the dragon at(m, n)
can be defended given two moves in a row. The first two moves to defend the dragon are given as(*ui, *uj)
and(*vi, *vj)
.
void goaldump(char goal[MAX_BOARD][MAX_BOARD])
quotation
Lists the goal array. For use in GDB:
(gdb) set goaldump(goal)
void owl_reasons(int color)
Add owl reasons. This function should be called once during genmove.
owl_does_defend(int ti, int tj, int m, int n)
Use the owl code to determine whether the move at(ti, tj)
makes the dragon at(m, n)
owl safe. This is used to test whether tactical defenses are strategically viable, whether a strategical defense move is effective, and whether a vital eye point does save an owl critical dragon.
owl_does_attack(int ti, int tj, int m, int n)
Use the owl code to determine whether the move at(ti, tj)
owl kills the dragon at(m, n)
. This is used to test whether strategical attack moves are dangerous enough to kill and whether a vital eye point does kill an owl critical dragon.
int owl_connection_defends(int ti, int tj, int ai, int aj, int bi, int bj)
Use the owl code to determine whether connecting the two dragons(ai, aj)
and(bi, bj)
by playing at(ti, tj)
results in a living dragon. Should be called only whenstackp==0
.
int owl_lively(int i, int j)
True unless(i, j)
isEMPTY
or occupied by a lunch for the goal dragon. Used duringmake_domains()
(seeoptics.c
: lively macro).
int owl_substantial(int i, int j)
This function, called whenstackp==0
, returns true if capturing the string at(i,j)
results in a live group.
int vital_chain(int m, int n)
This function returns true if it is judged that the capture of the
string at (m,n)
is sufficient to create one eye or to escape.
accumlate_influence()
engine/influence.c
We define lively stones to be all stones that can't be tactically attacked or have a tactical defense. Stones that have been found to be strategically dead are called dead while all other stones are called alive. If we want to use the influence function before deciding the strategical status, all lively stones count as alive.
Every alive stone on the board works as an influence source, with influence of its color radiating outwards in all directions. The strength of the influence declines exponentially with the distance from the source.
Influence can only flow unhindered if the board is empty, however. All lively stones (regardless of color) act as influence barriers, as do connections between enemy stones that can't be broken through. For example the one space jump counts as a barrier unless either of the stones can be captured. Notice that it doesn't matter much if the connection between the two stones can be broken, since in that case there would come influence from both directions anyway.
We define territory to be the intersections where one color has no influence at all and the other player does have. We can introduce moyo and area concepts similar to those provided by the Bouzy algorithms in terms of the influence values for the two colors. "Territory" refers to certain or probable territory while "Moyo" refers to an area of dominant influence which is not necessarily guaranteed territory. "Area" refers to the breathing space around a group in which it can manoever if it is attacked.
In order to avoid finding bogus territory, we add extra influence sources at places where an invasion can be launched, e.g. at 3-3 under a handicap stone, in the middle of wide edge extensions and in the center of large open spaces anywhere. Similarly we add extra influence sources where intrusions can be made into what otherwise looks as solid territory, e.g. monkey jumps.
Walls typically radiate an influence that is stronger than the sum of the influence from the stones building the wall. To accommodate for this phenomenon, we also add extra influence sources in empty space at certain distances away from walls.
The basic influence radiation process can efficiently be implemented as a breadth first search for adjacent and more distant points, using a queue structure.
Influence barriers can be found by pattern matching, assisted by reading through constraints and/or helpers. Wall structures, invasion points and intrusion points can be found by pattern matching as well.
When influence is computed, the basic idea is that there are a number of influence sources on the board, whose contributions are summed to produce the influence values. For the time being we can assume that the living stones on the board are the influence sources, although this is not the whole story.
The function compute_influence()
contains a loop over the
board, and for each influence source on the board, the function
accumulate_influence()
is called. This is the core of the
influence function. Before we get into the details, this is how
the influence field from a single isolated influence source of
strength 100 turns out:
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 2 3 2 1 0 0 0 0 0 1 3 5 11 5 3 1 0 0 0 1 2 5 16 33 16 5 2 1 0 0 1 3 11 33 X 33 11 3 1 0 0 1 2 5 16 33 16 5 2 1 0 0 0 1 3 5 11 5 3 1 0 0 0 0 0 1 2 3 2 1 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
These values are in reality floating point numbers but have been rounded down to the nearest integer for presentation. This means that the influence field does not stop when the numbers become zeroes.
Internally accumulate_influence()
starts at the influence source and
spreads influence outwards by means of a breadth first propagation,
implemented in the form of a queue. The order of propagation and the
condition that influence only is spread outwards guarantee that no
intersection is visited more than once and that the process
terminates. In the example above, the intersections are visited in the
following order:
+ + + + + + + + + + + + 78 68 66 64 63 65 67 69 79 + + 62 46 38 36 35 37 39 47 75 + + 60 34 22 16 15 17 23 43 73 + + 58 32 14 6 3 7 19 41 71 + + 56 30 12 2 0 4 18 40 70 + + 57 31 13 5 1 8 20 42 72 + + 59 33 21 10 9 11 24 44 74 + + 61 45 28 26 25 27 29 48 76 + + 77 54 52 50 49 51 53 55 80 + + + + + + + + + + + +
The visitation of intersections continues in the same way on the
intersections marked '+
and further outwards. In a real
position there will be stones and tight connections stopping the
influence from spreading to certain intersections. This will
disrupt the diagram above, but the main property of the
propagation still remains, i.e. no intersection is visited more
than once and after being visited no more influence will be
propagated to the intersection.
Let (m, n)
be the coordinates of the influence source and
(i, j)
the coordinates of a an intersection being visited
during propagation, using the same notation as in the
accumulate_influence()
function. Influence is now propagated to
its eight closest neighbors, including the diagonal ones,
according to the follow scheme:
For each of the eight directions (di, dj)
, do:
di*(i-m) + dj*(j-n)
between the vectors (di,dj)
and (i,j) - (m,n)
(i+di, j+dj)
is outside the board or occupied we
also continue with the next direction.
(i, j)
. The influence
propagated to (i+di, j+dj)
from this intersection is given by
P*(1/A)*D*S
, where the three different kinds of damping are:
P
, which is a property of the board
intersections. Normally this is one, i.e. unrestricted
propagation, but to stop propagation through e.g. one step
jumps, the permeability is set to zero at such intersections
through pattern matching. This is further discussed below.
A
, which is a property of the influence
source and different in different directions. By default this has the
value 3 except diagonally where the number is twice as much. By
modifying the attenuation value it is possible to obtain influence
sources with a larger or a smaller effective range.
D
, which is the squared cosine of the
angle between (di,dj)
and (i,j) - (m,n)
. The idea is to
stop influence from "bending" around an interfering stone and
get a continuous behavior at the right angle cutoff. The
choice of the squared cosine for this purpose is rather
arbitrary, but has the advantage that it can be expressed as a
rational function of m
, n
, i
, j
,
di
, and dj
, without involving any trigonometric or
square root computations. When we are visiting the influence
source we let by convention this factor be one.
Influence is typically contributed from up to three neighbors "between" this intersection and the influence source. These values are simply added together. As pointed out before, all contributions will automatically have been made before the intersection itself is visited.
When the total influence for the whole board is computed by
compute_influence()
, accumulate_influence()
is
called once for each influence source. These invocations are
totally independent and the influence contributions from the
different sources are added together.
The permeability at the different points is initially one at all empty intersections and zero at occupied intersections. To get a useful influence function we need to modify this, however. Consider the following position:
|...... |OOOO.. |...O.. |...a.X ('a' empty intersection) |...O.. |...OOO |.....O +------
The corner is of course secure territory for O
and clearly
the X
stone has negligible effect inside this position. To
stop X
influence from leaking into the corner we use pattern
matching (pattern Barrier1/Barrier2 in barriers.db
) to modify the
permeability for X
at this intersection to zero. O
can still
spread influence through this connection.
Another case that needs to be mentioned is how the permeability damping is computed for diagonal influence radiation. For horizontal and vertical radiation we just use the permeability (for the relevant color) at the intersection we are radiating from. In the diagonal case we additionally multiply with the maximum permeability at the two intersections we are trying to squeeze between. The reason for this can be found in the diagram below:
|...X |...X |OO.. |Oda. |..O. |.bc. |..O. |..O. +---- +----
We don't want X
influence to be spread from a
to
b
, and since the permeability at both c and d is zero, the
rule above stops this.
One application of the influence code is in computing the
dragon.escape_route
field. This is computed by the function
compute_escape()
as follows. First, every intersection is
assigned an escape value, ranging between 0 and 4, depending on
the influence value of the opposite color.
In addition to assiging an escape value to empty vertices, we also assign an escape value to friendly dragons. This value can range from 0 to 6 depending on the status of the dragon, with live dragons having value 6.
Then we sum the values of the resulting influence escape values over the intersections (including friendly dragons) at distance 4, that is, over those intersections which can be joined to the dragon by a path of length 4 (and no shorter path) not passing adjacent to any unfriendly dragon. In the following example, we sum the influence escape value over the four vertices labelled '4'.
. . . . . . . . . . . . . . . . . . . . . . . X . . O . . . . . X . . O . . X . . . . . O . . X . 2 . 4 . O X . . . . . . . . X . . 1 1 2 3 4 . X O . O . . . . O X O 1 O 1 2 3 4 O X O . O . . . . . X O 1 O 1 . 4 . . X O . . . X . O O X O 1 . . X . . O . . . X . . . . . . 1 . X . . . . . X . . . . X . . . X . . . . X . . . . . . . . . . . . . . . . . . . . .
Since the dragon is trying to reach safety, the reader might
wonder why compute_influence()
is called with the opposite
color of the dragon contemplating escape. To explain this point,
we first remind the reader why there is a color parameter to
compute_influence()
. Consider the following example position:
...XX... OOO..OOO O......O O......O --------
Whether the bottom will become O territory depends on who is in turn to play. This is implemented with the help of patterns in barriers.db, so that X influence is allowed to leak into the bottom if X is in turn to move but not if O is. There are also "invade" patterns which add influence sources in sufficiently open parts of the board which are handled differently depending on who is in turn to move.
In order to decide the territorial value of an O move in the third line gap above, influence is first computed in the original position with the opponent (i.e. X) in turn to move. Then the O stone is played to give:
...XX... OOO.OOOO O......O O......O --------
Now influence is computed once more, also this time with X in turn to move. The difference in territory (as computed from the influence values) gives the territorial value of the move.
Exactly how influence is computed for use in the escape route estimation is all ad hoc. But it makes sense to assume the opponent color in turn to move so that the escape possibilities aren't overestimated. After we have made a move in the escape direction it is after all the opponent's turn.
The current escape route mechanism seems good enough to be useful but is not completely reliable. Mostly it seems to err on the side of being too optimistic.
static void accumulate_influence(struct influence_data *q, int m, int n, int color)
Limited in scope to influence.c
, this is the core of the influence
function. Given the coordinates and color of an influence source, it radiates
the influence outwards until it hits a barrier or the strength of the
influence falls under a certain threshold. The radiation is performed by a
breadth first propagation, implemented by means of an internal queue.
void compute_initial_influence(int color, int dragons_known)
Compute the influence before a move has been made, which can later be compared to the influence after a move. Assume that the other color is in turn to move.
static void compute_move_influence(int m, int n, int color)
Let color play at (m, n) and compute the influence after this move, assuming that the other color is in turn to move next.
int influence_territory_color(int m, int n)
Return the color who has territory at (m, n), or EMPTY.
int influence_moyo_color(int m, int n)
Return the color who has moyo at (m, n), or EMPTY.
int influence_area_color(int m, int n)
Return the color who has area at (m, n), or EMPTY.
int influence_delta_territory(int m, int n, int color)
Compute the difference in territory made by a move by color at (m, n).
int influence_delta_moyo(int m, int n, int color)
Compute the difference in moyo made by a move by color at (m, n).
int influence_delta_strict_moyo(int m, int n, int color)
Compute the difference in strict moyo made by a move by color at (m, n).
int influence_delta_area(int m, int n, int color)
Compute the difference in area made by a move by color at (m, n).
int influence_delta_strict_area(int m, int n, int color)
Compute the difference in strict area made by a move by color at (m, n).
void debug_influence_move(int i, int j)
Print the influence map when we have computed influence for the move at (i, j).
It is possible to obtain colored diagrams showing influence from a colored xterm or rxvt window.
-m 0x08
or -m 8
Show diagrams for the initial influence computation. This is done
twice, the first time before make_dragons()
is run and the second time
after. The difference is that dead dragons are taken into account the
second time. Tactically captured worms are taken into account both
times.
-m 0x010
or -m 16
.
Show colored display of territory/moyo/area regions.Use either with
- territory: cyan
- moyo: yellow
- area: red
-m 0x8
(i.e. use-m 0x18
) or with--debuginfluence
.
-m 0x20
or -m 32
.
Show numerical influence values for white and black. These come in two separate diagrams, the first one for white, the second one for black. Notice that the influence values are represented by floats and thus have been rounded in these diagrams. Use either with-m 0x8
(i.e. use-m 0x28
) or with--debuginfluence
.
--debuginfluence location
Show influence diagrams after the move at the given location. An important limitation of this option is that it's only effective for moves that the move generation is considering.
-d 0x20
Turn on DEBUG_INFLUENCE
. This gives tons of messages from the pattern
matching performed by the influence code. Too many to be really
useful, unfortunately.
Notice that you need to activate at least one of -m 0x8
or
--debuginfluence
, and at least one of -m 0x10
and
-m 0x20
, to get any diagrams at all. The first two determine when to
print diagrams while the last two determine what diagrams to print.
moyo.c
and score.c
The file score.c
contains algorithms for the computation of
a number of useful things. Most can be displayed visually using
the -m
option (see Colored Display).
In GNU Go 2.6 extensive use was made of an algorithm from
Bruno Bouzy's dissertation, which is available at:
<ftp://www.joy.ne.jp/welcome/igs/Go/computer/bbthese.ps.Z
>
This algorithm starts with the characteristic function of the
live groups on the board and performs n
operations
called dilations, then m
operations called erosions.
If n=5 and m=21 this is called the 5/21 algorithm.
The Bouzy 5/21 algorithm is interesting in that it corresponds
reasonably well to the human concept of territory. This
algorithm is still used in GNU Go 3.0 in the function
estimate_score
. Thus we associate the 5/21 algorithm
with the word territory. Similarly we use words
moyo and area in reference to the 5/10
and 4/0 algorithms, respectively.
The principle defect of the algorithm is that it is not
tunable. The current method of estimating moyos and territory
is in influence.c
(see Influence). The territory,
moyo and area concepts have been reimplemented using the
influence code.
The Bouzy algorithm is briefly reimplemented in the file
scoring.c
and is used by GNU Go 3.0 in estimating
the score.
Not all features of the old moyo.c
from
GNU Go 2.6 were reimplemented--particularly the deltas were
not--but the reimplementation may be more readable.
Bouzy's algorithm was inspired by prior work of Zobrist and ideas from computer vision for determining territory. This algorithm is based on two simple operations, DILATION and EROSION. Applying dilation 5 times and erosion 21 times determines the territory.
To get a feeling for the algorithm, take a position in the early
middle game and try the colored display using the -m 1
option
in an RXVT window. The regions considered territory by this algorithm
tend to coincide with the judgement of a strong human player.
Before running the algorithm, dead stones (dragon.status==0
)
must be "removed."
Referring to page 86 of Bouzy's thesis, we start with a function taking a high value (ex : +128 for black, -128 for white) on stones on the goban, 0 to empty intersections. We may iterate the following operations:
dilation: for each intersection of the goban, if the intersection is >= 0, and not adjacent to a <0 one, then add to the intersection the number of adjacent >0 intersections. The same for other color : if the intersection is <=0, and not adjacent to a >0 one, then sub to it the number of <0 intersections.
erosion: for each intersection >0 (or <0), subtract (or add) the number of adjacent <=0 (or >=0) intersection. Stop at zero. The algorithm is just : 5 dilations, then 21 erosions. The number of erosions should be 1+n(n-1) where n=number of dilation, since this permit to have an isolated stone to give no territory. Thus the couple 4/13 also works, but it is often not good, for example when there is territory on the 6th line.
For example, let us start with a tobi.
128 0 128
1 dilation :
1 1 1 128 2 128 1 1 1
2 dilations :
1 1 2 2 3 2 2 1 2 132 4 132 2 1 2 2 3 2 2 1 1
3 dilations :
1 1 2 2 3 2 2 2 4 6 6 6 4 2 1 2 6 136 8 136 6 2 1 2 4 6 6 6 4 2 2 2 3 2 2 1 1
and so on...
Next, with the same example
3 dilations and 1 erosion :
2 2 2 0 4 6 6 6 4 0 2 6 136 8 136 6 2 0 4 6 6 6 4 2 2 2
3 dilations and 2 erosions :
1 2 6 6 6 2 6 136 8 136 6 2 6 6 6 2 1
3 dil. / 3 erosions :
5 6 5 5 136 8 136 5 5 6 5
3/4 :
3 5 3 2 136 8 136 2 3 5 3
3/5 :
1 4 1 136 8 136 1 4 1
3/6 :
3 135 8 135 3
3/7 :
132 8 132
We interpret this as a 1 point territory.
In this Chapter, we document some of the utilities which may be called from the GNU Go engine. If there are differences between this documentation and the source files, the source files are the ultimate reference. You may find it convenient to use Emacs' built in facility for navigating the source to find functions and their in-source documentation (see Navigating the Source).
engine/utils.c
engine/printutils.c
Utility functions from engine/utils.c
. Many of these
functions underlie autohelper functions (see Autohelper Functions).
void change_dragon_status(int x, int y, int status)
Change the status of the dragon at (x,y)
.
void count_territory( int *white, int *black)
Measure territory.
void evaluate_territory( int *white, int *black)
Evaluate territory for both sides. Removes dead dragons before counting. The position cannot be reused after this operation.
void change_defense(int ai, int aj, int ti, int tj, int dcode)
Moves the point of defense of(ai, aj)
to(ti, tj)
, and setsworm[a].defend_code
todcode
.
void change_attack(int ai, int aj, int ti, int tj, int acode)
Moves the point of attack of the worm at(ai, aj)
to(ti, tj)
, and setsworm[a].attack_code
toacode
.
int defend_against(int ti, int tj, int color, int ai, int aj)
Returns true if a move at(ti,tj)
prevents the enemy from playing at(ai,aj)
. It is checked whether after the movest
,a
, the string ata
can be captured.
int cut_possible(int i, int j, int color)
Returns true ifcolor
can cut at(i,j)
. This information is collected byfind_cuts()
, using theB
patterns in the connections database.
int does_attack(int ti, int tj, int ai, int aj)
Returns true if the move at(ti, tj)
attacks(ai, aj)
. This means that it captures the string, and that(ai, aj)
is not already dead.
int does_defend(int ti, int tj, int ai, int aj)
Returns true if the move at(ti, tj)
defends(ai, aj)
. This means that it defends the string, and that(ai, aj)
can be captured if no defense is made.
int somewhere(int color, int last_move, ...)
Example:somehere(WHITE, 2, ai, aj, bi, bj, ci, cj).returns true if one of the vertices listed satisfies
p[i][j]==color
. Here last_move is the number of moves minus one.
int play_break_through_n(int color, int num_moves, ...)
This function plays a sequence of moves, alternating between the players and starting with color. After having played through the sequence, the three last coordinate pairs gives a position to be analyzed bybreak_through()
, to see whether either color has managed to enclose some stones and/or connected his own stones. If any of the three last positions is empty, it's assumed that the enclosure has failed, as well as the attempt to connect. If one or more of the moves to play turns out to be illegal for some reason, the rest of the sequence is played anyway, andbreak_through()
is called as if nothing special happened. Likebreak_through()
, this function returns 1 if the attempt to break through was succesful and 2 if it only managed to cut through. The functionbreak_through
is documented elsewhere (see Reading Functions).
int play_break_through_n(int color, int num_moves, ...)
plays a sequence of moves, alternating between the players and starting with color. After having played through the sequence, the three last coordinate pairs gives a position to be analyzed by break_through(), to see whether either color has managed to enclose some stones and/or connected his own stones. If any of the three last positions is empty, it's assumed that the enclosure has failed, as well as the attempt to connect. If one or more of the moves to play turns out to be illegal for some reason, the rest of the sequence is played anyway, and break_through() is called as if nothing special happened. Like break_through(), this function returns 1 if the attempt to break through was succesful and 2 if it only managed to cut through.
int play_attack_defend_n(int color, int do_attack, int num_moves, ...)
Plays a sequence of moves, alternating between the players and starting with color. After having played through the sequence, the last coordinate pair gives a target to attack or defend, depending on the value of do_attack. If there is no stone present to attack or defend, it is assumed that it has already been captured. If one or more of the moves to play turns out to be illegal for some reason, the rest of the sequence is played anyway, and attack/defense is tested as if nothing special happened. A typical use for these functions is to set up a ladder in an autohelper and see whether it works or not.
int play_attack_defend2_n(int color, int do_attack, int num_moves, ...)
The function play_attack_defend2_n() plays a sequence of moves, alternating between the players and starting with color. After having played through the sequence, the two last coordinate pairs give two targets to simultaneously attack or defend, depending on the value of do_attack. If there is no stone present to attack or defend, it is assumed that it has already been captured. If one or more of the moves to play turns out to be illegal for some reason, the rest of the sequence is played anyway, and attack/defense is tested as if nothing special happened. A typical use for these functions is to set up a crosscut in an autohelper and see whether at least one cutting stone can be captured.
int find_lunch(int m, int n, int *wi, int *wj, int *ai, int *aj)
Looks for a worm adjoining the string at(m,n)
which can be easily captured. Whether or not it can be defended doesn't matter (see Worms and Dragons). Returns the location of the string in(*wi, *wj)
, and the location of the attacking move in(*ai, *aj)
.
void modify_depth_values(int n)
The parametersdepth
,backfill_depth
,fourlib_depth
andko_depth
are incremented byn
. This is typically used to avoid horizon effects. By temporarily increasing the depth values when trying some move, one can avoid that an irrelevant move seems effective just because the reading hits a depth limit earlier than it did when reading only on relevant moves.
void increase_depth_values(void)
Same as modify_depth_values(1)
.
void decrease_depth_values(void)
Same as modify_depth_values(-1)
.
void set_temporary_depth_values(int d, int b, int f, int k)
void restore_depth_values()
These functions allow more drastic temporary modifications of the depth values. Typical use is to turn certain depth values way down for reading where speed is more important than accuracy, e.g. for the influence function. Temporarily set or restore the values ofdepth
,backfill_depth
,fourlib_depth
ko_depth
.
int same_dragon(int ai, int aj, int bi, int bj)
Test whether two dragons are the same. Used by autohelpers.
int same_worm(int ai, int aj, int bi, int bj)
Test whether two worms are the same. Used by autohelpers.
int is_worm_origin(int wi, int wj, int i, int j)
Determine whether two worms have the same origin.
int accurate_approxlib(int m, int n, int color, int maxlib, int *libi, int *libj)
Play a stone at(m, n)
and count the number of liberties for the resulting string. This requires(m, n)
to be empty. This function differs fromapproxlib()
by the fact that it removes captured stones before counting the liberties. Iflibi != NULL
the found liberties are written into thelibi[], libj[]
arrays, but no more thanmaxlib
of them. Liberties exceedingmaxlib
may or may not be reported in the return value. If you want to know the exact number of liberties, regardless how large, you should setmaxlib
toMAXLIBS
.
int confirm_safety(int i, int j, int color, int value, int *di, int *dj)
This function will detect some blunders. Returns 1 if a move bycolor
at(i,j)
does not diminish the safety of any worm, nor tend to rescue inadvertantly an opponent stone.
int double_atari(int m, int n, int color)
Returns true if a move by (color) fits the following shape:. X*. (O=color) OXcapturing one of the two X strings. The name is a slight misnomer since this includes attacks which are not necessarily double ataris, though the common double atari is the most important special case.
int unconditional_life(int wormi[MAX_STRINGS], int wormj[MAX_STRINGS], int color)
Find those worms of the given color that can never be captured, even if the opponent is allowed an arbitrary number of consecutive moves. The coordinates of the origins of these worms are written to the wormi, wormj arrays and the number of non-capturable worms is returned. The algorithm is to cycle through the worms until none remains or no more can be captured. A worm is removed when it is found to be capturable, by letting the opponent try to play on all its liberties. If the attack fails, the moves are undone.
int vital_chain(int m, int n)
This function returns true if it is judged that the capture of the string at (m,n) is sufficient to create one eye. The current just checks that (m,n) is not a singleton on the first line. For use when called from fill_liberty, this function may optionally return a point(*di, *dj)
of defense, which, if taken, will presumably make the move at(i, j)
safe on a subsequent turn.
double gg_gettimeofday(void)
Get the time of day, callinggettimeofday
fromsys/time.h
if available, otherwise substituting a workaround for portability.
void sniff_lunch(int i, int j, int *max, int *min)
Computes the number of eyes yielded by capturing a lunch. The surrounding liberties are filled and the stones are removed from the board. Then compute_eyes is called to evaluate the resulting eyespace. The maximum and minimum number of resulting eyes is returned in the variables *max and *min.
int unconditional_life(int wormi[MAX_STRINGS], int wormj[MAX_STRINGS], int color)
Find those worms of the given color that can never be captured, even if the opponent is allowed an arbitrary number of consecutive moves. The coordinates of the origins of these worms are written to thewormi
,wormj
arrays and the number of non-capturable worms is returned.
Utility functions from engine/printutils.c
.
static void vgprintf(FILE* outputfile, const char *fmt, va_list ap)
This function underpins all theTRACE
andDEBUG
stuff. It is static toprintutils.c
but documented here for completeness. Accepts%c
,%d
,%f
,%s
, and%x
as usual. But it also accepts%m
, which takes TWO integers and writes a move. Other nonstandard format strings are%H
for writing a hash value and%C
to convert a color value into a string.%o
at start means outdent (ie cancel indent). The scope of this function is limited toengine/utils.c
but the format codes%m
and%c
$ work for all its relatives such asTRACE
.
void gprintf(const char *fmt, ...)
Required wrapper tovgprintf
. Writes tostderr
.
void mprintf(const char *fmt, ...)
Identical togprintf
except that it prints tostdout
. Useful when%m
is needed for non-error messages, e.g. in the ascii interface.
void TRACE(const char *fmt, ...)
Basic tracing function. Likegprintf
but prints only ifverbose>0
. Set theverbose
level with the-t
option (see Invoking GNU Go). VariantsRTRACE
, etc. are documented in the source.
void DEBUG(int flag, const char *fmt, ...)
LikeTRACE
but conditioned on a debug flag being set, usually at the command line with-d
option (see Invoking GNU Go).
void abortgo(const char *file, int line, const char *msg, int x, int y)
A wrapper aroundabort()
which shows the state variables at the time of the problem.(i, j)
are typically a related move, or-1, -1
.
ASSERT
This is the usual way of callingabortgo
. This macro (defined inliberty.h
) terminates the program ifcondition
fails.
const char *color_to_string(int color)
Convert a color value to a string.
const char * location_to_string(int i, int j)
Converts a board location to a string
const char * status_to_string(int i, int j)
Converts a status to a string.
The algorithms in board.c
implement a method of incremental board
updates that keeps track of the following information for each string:
i
coordinate and if there is a tie with
smallest j
coordinate.
The basic data structure is
struct string_data { int color; /* Color of string, BLACK or WHITE */ int size; /* Number of stones in string. */ int origini; /* Coordinates of "origin", i.e. */ int originj; /* "upper left" stone. */ int liberties; /* Number of liberties. */ int libi[MAX_LIBERTIES]; /* Coordinates of liberties. */ int libj[MAX_LIBERTIES]; int neighbors; /* Number of neighbor strings */ int neighborlist[MAXCHAIN]; /* List of neighbor string numbers. */ int mark; /* General purpose mark. */ }; struct string_data string[MAX_STRINGS];
It should be clear that almost all information is stored in the
string
array. To get a mapping from the board coordinates to the
string
array we have
int string_number[MAX_BOARD][MAX_BOARD];
which contains indices into the string
array. This information is only
valid at nonempty vertices, however, so it is necessary to first
verify that p[i][j] != EMPTY
.
The string_data
structure does not include an array of the stone
coordinates. This information is stored in a separate array (or rather
two):
int next_stonei[MAX_BOARD][MAX_BOARD]; int next_stonej[MAX_BOARD][MAX_BOARD];
These arrays implement cyclic linked lists of stones. Each vertex contains a pointer to another (possibly the same) vertex. Starting at an arbitrary stone on the board, following these pointers should traverse the entire string in an arbitrary order before coming back to the starting point. As for the 'string_number' array, this information is invalid at empty points on the board. This data structure has the good properties of requiring fixed space (regardless of the number of strings) and making it easy to add a new stone or join two strings.
Additionally the code makes use of some work variables:
static int ml[MAX_BOARD][MAX_BOARD]; static int liberty_mark; static int string_mark; static int next_string; static int strings_initialized = 0;
The ml
array and liberty_mark
are used to "mark" liberties on
the board, e.g. to avoid counting the same liberty twice. The convention is
that if ml[i][j]
has the same value as liberty_mark
, then
(i, j)
is marked. To clear all marks it suffices to increase the value
of liberty_mark
, since it is never allowed to decrease.
The same relation holds between the mark
field of the string_data
structure and string_mark
. Of course these are used for marking
individual strings.
next_string
gives the number of the next available entry in the
string
array. Then strings_initialized
is set to one when
all data structures are known to be up to date. Given an arbitrary board
position in the p
array, this is done by calling
incremental_board_init()
. It is not necessary to call this
function explicitly since any other function that needs the information
does this if it has not been done.
The interesting part of the code is the incremental update of the data structures when a stone is played and subsequently removed. To understand the strategies involved in adding a stone it is necessary to first know how undoing a move works. The idea is that as soon as some piece of information is about to be changed, the old value is pushed onto a stack which stores the value and its address. The stack is built from the following structures:
struct change_stack_entry { int *address; int value; }; struct change_stack_entry change_stack[STACK_SIZE]; int change_stack_index;
and manipulated with the macros
BEGIN_CHANGE_RECORD() PUSH_VALUE(v) POP_MOVE()
Calling BEGIN_CHANGE_RECORD()
stores a null pointer in the address
field to indicate the start of changes for a new move. As mentioned
earlier PUSH_VALUE()
stores a value and its corresponding address.
Assuming that all changed information has been duly pushed onto the
stack, undoing the move is only a matter of calling POP_MOVE()
,
which simply assigns the values to the addresses in the reverse order
until the null pointer is reached. This description is slightly
simplified because this stack can only store 'int' values and we need
to also store changes to the board. Thus we have two parallel stacks
where one stores int
values and the other one stores
Intersection
values.
When a new stone is played on the board, first captured opponent
strings, if any, are removed. In this step we have to push the board
values and the next_stone
pointers for the removed stones, and
update the liberties and neighbor lists for the neighbors of the
removed strings. We do not have to push all information in the
'string' entries of the removed strings however. As we do not reuse
the entries they will remain intact until the move is pushed and they
are back in use.
After this we put down the new stone and get three distinct cases:
The first case is easiest. Then we create a new string by using the
number given by next_string
and increasing this variable. The string
will have size one, next_stone
points directly back on itself, the
liberties can be found by looking for empty points in the four
directions, possible neighbor strings are found in the same way, and
those need also to remove one liberty and add one neighbor.
In the second case we do not create a new string but extend the neighbor with the new stone. This involves linking the new stone into the cyclic chain, if needed moving the origin, and updating liberties and neighbors. Liberty and neighbor information also needs updating for the neighbors of the new stone.
In the third case finally, we need to join already existing strings. In order not to have to store excessive amounts of information, we create a new string for the new stone and let it assimilate the neighbor strings. Thus all information about those can simply be left around in the 'string' array, exactly as for removed strings. Here it becomes a little more complex to keep track of liberties and neighbors since those may have been shared by more than one of the joined strings. Making good use of marks it all becomes rather straightforward anyway.
The often used construction
FIRST_STONE(s, i, j); do { ... NEXT_STONE(i, j); } while (!BACK_TO_FIRST_STONE(s, i, j));
traverses the stones of the string with number s
exactly once,
with (i, j)
holding the coordinates. In general (i, j)
are
used as board coordinates and s
as an index into the
string
array or sometimes a pointer to an entry in the
string
array.
GNU Go 3.0 introduces a new interface, the Go Text Protocol (GTP). The intention is to make an interface that is better suited for machine-machine communication than the ascii interface and simpler, more powerful, and more flexible than the Go Modem Protocol.
The GTP has two principal current applications: it is used
in the test suite (see Regression) and it is used to
communicate with gnugoclient
, which is not part
of the GNU Go distribution, but has been used to run GNU
Go on NNGS. Other potential uses might be any of the current
uses of the GMP, for which the GTP might serve as a replacement.
This would likely entail extension and standardization of
the protocol.
A sample GTP session may look as follows:
hannah 2289% ./interface/gnugo --quiet --mode gtp 1 loadsgf regression/games/incident156.sgf 249 =1 2 countlib C3 =2 4 3 findlib C3 =3 C4 B3 D3 B2 5 attack C3 =5 0 owl_attack C3 = 1 B4 3 owl_defend C3 =3 1 B5 owl_attack A2 ? vertex must not be empty quit =
By specifying --mode gtp
GNU Go starts in the GTP
interface. No prompt is used, just start giving commands. The
commands have the common syntax
[id] command_name [arguments]
The command is exactly one line long, i.e. it ends as soon as a newline appears. It's not possible to give multiple commands on the same line. Before the command name an optional identity number can be specified. If present it must be an integer between 0 and 2^31-1. The id numbers may come in any order or be reused. The rest of the line after the command name is assumed to be arguments for the command. Empty lines are ignored, as is everything following a hash sign up to the end of the line.
If the command is successful, the response is of the form
=[id] result
Here =
indicates success and id
is the identity
number given in the command or the empty string if the id was
omitted. This is followed by the result, which is a text string
ending with two consecutive newlines.
If the command fails for some reason, the response takes the form
?[id] error_message
Here ?
indicates failure, id
is as before, and
error_message
gives an explanation for the failure. This
string also ends with two consecutive newlines.
The available commands may always be listed using the single command
help
. Currently this gives the list below.
attack black boardsize color combination_attack countlib debug_influence debug_move_influence decrease_depths defend dragon_data dragon_status dump_stack echo eval_eye final_score findlib fixed_handicap genmove_black genmove_white get_life_node_counter get_owl_node_counter get_reading_node_counter get_trymove_counter gg_genmove help increase_depths influence is_legal komi level loadsgf move_influence name new_score owl_attack owl_defend popgo prisoners quit report_uncertainty reset_life_node_counter reset_owl_node_counter reset_reading_node_counter reset_trymove_counter same_dragon showboard trymove tune_move_ordering version white worm_cutstone worm_data
For exact specification of their arguments and results we refer to the
comments of the functions in interface/play_gtp.c
.
The protocol is asymmetric and involves two parties, which we may
call A
and B
. A
is typically some kind of arbiter or
relay and B
is a go engine. All communication is initiated by A
in form of commands, to which B
responds.
Potential setups include:
A (regression script) -- B (engine).
A sets up a board position and asks B to e.g. generate a move or find an attack on a specific string.
A (GUI) -- B (engine)
The GUI relays moves between the human and the engine and asks the engine to generate moves. Optionally the GUI may also use GTP to ask the engine which moves are legal or give a score when the game is finished.
B1 (engine 1) -- A (arbiter) -- B2 (engine 2)
A relays moves between the two engines and alternately asks the engines to generate moves. This involves two different GTP channels, the first between A and B1, and the second between A and B2. There is no direct communication between B1 and B2. The arbiter dictates board size, komi, rules, etc.
The same as above except that B1 includes the arbiter functionality and the first GTP link is shortcut.
Go server -- A (relay) -- B (engine)
A talks with a go server using whatever protocol is needed and listens for match requests. When one arrives it accepts it, starts the go engine and issues GTP commands to set up board size, komi, etc. and if a game is restarted it also sets up the position. Then it relays moves between the server and the engine and asks the engine to generate new moves when it is in turn.
Setups 1 and 5 are in active and regular use with GNU Go. Programs
implementing setup 3 are also distributed with GNU Go (the files
interface/gtp_examples/twogtp
and
interface/gtp_examples/2ptkgo.pl
).
The GTP is currently unfinished and unstandardized. It is hoped that it will grow to fill the needs currently served by the GMP and perhaps other functions. As it is yet unstandardized, this section gives some general remarks which we hope will constrain its development. We also discuss how the GTP is implemented in GNU Go, for the benefit of anyone wishing to add new commands. Notice that the current set of GTP commands is a mix of generally useful ones and highly GNU Go specific ones. Only the former should be part of a standardized protocol while the latter should be private extensions.
The purpose of the protocol is machine-machine communication. It may be tempting to modify the protocol so that it becomes more comfortable for the human user, for example with an automatic showboard after every move. This is absolutely not the purpose of the protocol! Use the ascii interface instead if you're inclined to make such a change.
Newlines are implemented differently on different operating systems. On Unix, a newline is just a line feed LF (ascii \012). On DOS/Windows it is CRLF (\013\012). Thus whether GNU Go sends a carriage return with the line feed depends on which platform it is compiled for. The arbiter should silently discard carriage returns.
Applications using GTP should never have to guess about the basic
structure of the responses, defined above. The basic construction for
coding a GTP command can be found in gtp_countlib()
:
static int gtp_countlib(char *s, int id) { int i, j; if (!gtp_decode_coord(s, &i, &j)) return gtp_failure(id, "invalid coordinate"); if (p[i][j] == EMPTY) return gtp_failure(id, "vertex must not be empty"); return gtp_success(id, "%d", countlib(i, j)); }
The functions gtp_failure()
and gtp_success()
automatically ensures the specified response format, assuming the
strings they are printing do not end with a newline.
Sometimes the output is too complex for use with gtp_success, e.g. if
we want to print vertices, which gtp_success() doesn't
support. Then we have to fall back to the construction in e.g.
gtp_genmove_white()
:
static int gtp_genmove_white(char *s, int id) { int i, j; UNUSED(s); if (genmove(&i, &j, WHITE) >= 0) play_move(i, j, WHITE); gtp_printid(id, GTP_SUCCESS); gtp_print_vertex(i, j); return gtp_finish_response(); }
Here gtp_printid()
writes the equal sign and the request id while
gtp_finish_response()
adds the final two newlines. The next example
is from gtp_influence()
:
gtp_printid(id, GTP_SUCCESS); get_initial_influence(color, 1, white_influence, black_influence, influence_regions); print_influence(white_influence, black_influence, influence_regions); /* We already have one newline, thus can't use gtp_finish_response(). */ gtp_printf("\n"); return GTP_OK;
As we have said, the response should be finished with two newlines. Here we have to finish up the response ourselves since we already have one newline in place.
One problem that can be expected to be common is that an engine happens to finish its response with three (or more) rather than two consecutive newlines. This is an error by the engine that the controller can easily detect and ignore. Thus a well behaved engine should not send stray newlines, but should they appear the controller should ignore them. The opposite problem of an engine failing to properly finish its response with two newlines will result in deadlock. Don't do this mistake!
Although it doesn't suffice in more complex cases, gtp_success() is by
far the most convenient construction when it does. For example,
the function gtp_report_uncertainty
takes a single argument
which is expected to be "on" or "off", after which it sets the
value of report_uncertainty
, a variable which affects
the form of future GTP responses, reports success, and exits. The
function is coded thus:
static int gtp_report_uncertainty(char *s, int id) { if (!strncmp(s, "on", 2)) { report_uncertainty = 1; return gtp_success(id, ""); } if (!strncmp(s, "off", 3)) { report_uncertainty = 0; return gtp_success(id, ""); } return gtp_failure(id, "invalid argument"); }
GNU Go uses GTP for regression testing. These tests are implemented as files with GTP commands, which are fed to GNU Go simply by redirecting stdin to read from a file. The output is filtered so that equal signs and responses from commands without id numbers are removed. These results are then compared with expected results encoded in GTP comments in the file, using matching with regular expressions. More information can be found in the regression chapter (see Regression).
The standard purpose of regression testing is to avoid getting the same bug twice. When a bug is found, the programmer fixes the bug and adds a test to the test suite. The test should fail before the fix and pass after the fix. When a new version is about to be released, all the tests in the regression test suite are run and if an old bug reappears, this will be seen quickly since the appropriate test will fail.
The regression testing in GNU Go is slightly different. A typical test case involves specifying a position and asking the engine what move it would make. This is compared to one or more correct moves to decide whether the test case passes or fails. It is also stored whether a test case is expected to pass or fail, and deviations in this status signify whether a change has solved some problem and/or broken something else. Thus the regression tests both include positions highlighting some mistake being done by the engine, which are waiting to be fixed, and positions where the engine does the right thing, where we want to detect if a change breaks something.
Regression testing is performed by the files in the regression/
directory. The tests are specified as GTP commands in files with the
suffix .tst
, with corresponding correct results and expected
pass/fail status encoded in GTP comments following the test. To run a
test suite the shell scripts test.sh
, eval.sh
, and
regress.sh
can be used. There are also Makefile targets to do
this. If you make all_batches
most of the tests are run.
Game records used by the regression tests are stored in the
directory regression/games/
and its subdirectories.
The regression tests are grouped into suites and stored in files as GTP commands. A part of a test suite can look as follows:
# Connecting with ko at B14 looks best. Cutting at D17 might be # considered. B17 (game move) is inferior. loadsgf games/strategy25.sgf 61 90 gg_genmove black #? [B14|D17] # The game move at P13 is a suicidal blunder. loadsgf games/strategy25.sgf 249 95 gg_genmove black #? [!P13] loadsgf games/strategy26.sgf 257 100 gg_genmove black #? [M16]*
Lines starting with a hash sign, or in general anything following a hash
sign, are interpreted as comments by the GTP mode and thus ignored by
the engine. GTP commands are executed in the order they appear, but only
those on numbered lines are used for testing. The comment lines starting
with #?
are magical to the regression testing scripts and
indicate correct results and expected pass/fail status. The string
within brackets is matched as a regular expression against the response
from the previous numbered GTP command. A particular useful feature of
regular expressions is that by using |
it is possible to specify
alternatives. Thus B14|D17
above means that if either B14
or D17
is the move generated in test case 90, it passes. There is
one important special case to be aware of. If the correct result string
starts with an exclamation mark, this is excluded from the regular
expression but afterwards the result of the matching is negated. Thus
!P13
in test case 95 means that any move except P13
is
accepted as a correct result.
In test case 100, the brackets on the #?
line is followed by an
asterisk. This means that the test is expected to fail. If there is no
asterisk, the test is expected to pass. The brackets may also be
followed by a &
, meaning that the result is ignored. This is
primarily used to report statistics, e.g. how many tactical reading
nodes were spent while running the test suite.
./test.sh blunder.tst
runs the tests in blunder.tst
and
prints the results of the commands on numbered lines, which may look
like:
1 E5 2 F9 3 O18 4 B7 5 A4 6 E4 7 E3 8 A3 9 D9 10 J9 11 B3 12 C6 13 C6
This is usually not very informative, however. More interesting is
./eval.sh blunder.tst
which also compares the results above
against the correct ones in the test file and prints a report for each
test on the form:
1 failed: Correct '!E5', got 'E5' 2 failed: Correct 'C9|H9', got 'F9' 3 PASSED 4 failed: Correct 'B5|C5|C4|D4|E4|E3|F3', got 'B7' 5 PASSED 6 failed: Correct 'D4', got 'E4' 7 PASSED 8 failed: Correct 'B4', got 'A3' 9 failed: Correct 'G8|G9|H8', got 'D9' 10 failed: Correct 'G9|F9|C7', got 'J9' 11 failed: Correct 'D4|E4|E5|F4|C6', got 'B3' 12 failed: Correct 'D4', got 'C6' 13 failed: Correct 'D4|E4|E5|F4', got 'C6'
The result of a test can be one of four different cases:
passed
: An expected pass
This is the ideal result.
PASSED
: An unexpected pass
This is a result that we are hoping for when we fix a bug. An old test case that used to fail is now passing.
failed
: An expected failure
The test failed but this was also what we expected, unless we were trying to fix the particular mistake highlighted by the test case. These tests show weaknesses of the GNU Go engine and are good places to search if you want to detect an area which needs improvement.
FAILED
: An unexpected failure
This should nominally only happen if something is broken by a change. However, sometimes GNU Go passes a test, but for the wrong reason or for a combination of wrong reasons. When one of these reasons is fixed, the other one may shine through so that the test suddenly fails. When a test case unexpectedly fails, it is necessary to make a closer examination in order to determine whether a change has broken something.
If you want a less verbose report, ./regress.sh . blunder.tst
does the same thing as the previous command, but only reports unexpected
results. The example above is compressed to
3 unexpected PASS! 5 unexpected PASS! 7 unexpected PASS!
For convenience the tests are also available as makefile targets. For
example, make blunder
runs the tests in the blunder test suite by
executing eval.sh blunder.tst
. make test
runs all test
suites in a sequence using the regress.sh
script.
The program GNU Go is distributed under the terms of the GNU General Public License (GPL). Its documentation is distributed under the terms of the GNU Free Documentation License (GFDL).
Version 2, June 1991
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accumulate_influence
: Influential Functions
accurate_approxlib
: General Utilities
add_antisuji_move
: Move Generation Functions
add_attack_either_move
: Move Generation Functions
add_block_territory_move
: Move Generation Functions
add_connection_move
: Move Generation Functions
add_cut_move
: Move Generation Functions
add_defend_both_move
: Move Generation Functions
add_defense_move
: Move Generation Functions
add_expand_moyo_move
: Move Generation Functions
add_expand_territory_move
: Move Generation Functions
add_followup_value
: Move Generation Functions
add_half_eye
: Eye Functions
add_lunch
: Move Generation Functions
add_move_reason
: Local MG Functions
add_semeai_move
: Move Generation Functions
add_shape_value
: Move Generation Functions
add_stone
: Board Setup Functions
add_strategical_attack_move
: Move Generation Functions
add_strategical_defense_move
: Move Generation Functions
add_vital_eye_move
: Move Generation Functions
amalgamate_most_valuable_helper
: Connection
approxlib
: String Functions
ASSERT
: Print Utilities
atari_atari
: Reading Functions, Combination Attacks, Move Generation Basics
atari_atari_confirm_safety
: Reading Functions
atari_atari_try_combination
: Reading Functions
attack
: Reading Functions, Reading Basics
attack2
: Reading Basics
attack3
: Reading Basics
attack4
: Reading Basics
attack_and_defend
: Reading Functions
attack_either
: Reading Functions
attack_move_known
: Move Generation Functions
break_chain
: Reading Basics
break_chain2
: Reading Basics
break_through
: Reading Functions
chainlinks
: String Functions
chainlinks2
: String Functions
change_attack
: General Utilities
change_defense
: General Utilities
change_dragon_status
: General Utilities
clear_board
: Board Setup Functions
clear_move_reasons
: Move Generation Functions
compute_dragon_status
: Worm and Dragon Functions
compute_escape_potential
: Worm and Dragon Functions
compute_eyes
: Eye Functions
compute_eyes_pessimistic
: The Owl Code, Eye Functions
compute_initial_influence
: Influential Functions, Move Generation Basics
compute_move_influence
: Influential Functions
confirm_safety
: General Utilities
connection_value2
: Local MG Functions
countlib
: String Functions
countstones
: String Functions
cut_connect_callback
: Connection Functions
cut_possible
: General Utilities
debug_influence_move
: Influential Functions
decrease_depth_values
: General Utilities
defend1
: Reading Basics
defend2
: Reading Basics
defend3
: Reading Basics
defend_against
: General Utilities
defense_move_known
: Move Generation Functions
do_remove_false_attack_and_defense_moves
: Local MG Functions
does_attack
: General Utilities
does_capture_something
: Status Functions
does_defend
: General Utilities
double_atari
: General Utilities
dragon_eye
: Amalgamation
dragon_safety
: Local MG Functions
dump_stack
: Move Functions
effective_dragon_size
: Local MG Functions
endgame_shapes
: Sequence of Events, Move Generation Basics
estimate_influence_value
: Local MG Functions, Influence value
estimate_strategical_value
: Local MG Functions
estimate_territorial_value
: Local MG Functions, Territorial value
evaluate_diagonal_intersection
: Eye Functions
examine_cavity
: Worm and Dragon Functions
examine_position
: Move Generation Basics
eye_space
: Eye Functions
fill_liberty
: Move Generation Basics
find_cap2
: Reading Basics
find_connection
: Local MG Functions
find_connections
: Connection Functions
find_cuts
: Connection Functions
find_defense
: Reading Functions, Reading Basics
find_dragon
: Local MG Functions
find_eye
: Local MG Functions
find_lunch
: General Utilities
find_more_attack_and_defense_moves
: Local MG Functions
find_origin
: String Functions
find_reason
: Local MG Functions
find_semeai
: Local MG Functions
find_worm
: Local MG Functions
find_worm_pair
: Local MG Functions
findlib
: String Functions
findstones
: String Functions
followup
: Pattern Values
fuseki
: Move Generation Basics
gameinfo_clear
: Positional Functions
gameinfo_load_sgfheader
: Positional Functions
gameinfo_play_move
: Positional Functions
gameinfo_play_sgftree
: Positional Functions
gameinfo_print
: Positional Functions
gameinfo_undo_move
: Positional Functions
genmove
: Move Generation Basics
get_move_from_stack
: Move Functions
get_read_result
: Hash Functions
get_trymove_counter
: Move Functions
gg_gettimeofday
: General Utilities
gnugo_add_stone
: Positional Functions
gnugo_attack
: Positional Functions
gnugo_clear_position
: Positional Functions
gnugo_copy_position
: Positional Functions
gnugo_estimate_score
: Positional Functions
gnugo_examine_position
: Positional Functions
gnugo_find_defense
: Positional Functions
gnugo_force_to_globals
: Positional Functions
gnugo_genmove
: Positional Functions
gnugo_is_legal
: Positional Functions
gnugo_is_suicide
: Positional Functions
gnugo_placehand
: Positional Functions
gnugo_play_move
: Positional Functions
gnugo_play_sgfnode
: Positional Functions
gnugo_play_sgftree
: Positional Functions
gnugo_recordboard
: Positional Functions
gnugo_remove_stone
: Positional Functions
gnugo_sethand
: Positional Functions
gnugo_who_wins
: Positional Functions
goaldump
: Owl Functions
hashdata_compare
: Hash Functions
hashdata_diff_dump
: Hash Functions
hashdata_invert_stone
: Hash Functions
hashdata_recalc
: Hash Functions
hashdata_remove_ko
: Hash Functions
hashdata_set_ko
: Hash Functions
hashnode_dump
: Hash Functions
hashnode_new_result
: Hash Functions, Hash Organization
hashnode_search
: Hash Functions
hashposition_dump
: Hash Functions
hashtable_clear
: Hash Functions
hashtable_clear_if_full
: Hash Functions
hashtable_dump
: Hash Functions
hashtable_enter_position
: Hash Functions, Hash Organization
hashtable_init
: Hash Functions
hashtable_new
: Hash Functions
hashtable_search
: Hash Functions, Hash Organization
increase_depth_values
: General Utilities
incremental_order_moves
: String Functions
induce_secondary_move_reasons
: Local MG Functions
influence_area_color
: Influential Functions
influence_delta_area
: Influential Functions
influence_delta_moyo
: Influential Functions
influence_delta_strict_area
: Influential Functions
influence_delta_strict_moyo
: Influential Functions
influence_delta_territory
: Influential Functions
influence_moyo_color
: Influential Functions
influence_territory_color
: Influential Functions
init_gnugo
: Getting Started
is_antisuji_move
: Local MG Functions
is_illegal_ko_capture
: Status Functions
is_ko
: Status Functions
is_legal
: Status Functions, Roadmap
is_pass
: Status Functions
is_self_atari
: Status Functions
is_suicide
: Status Functions
is_worm_origin
: General Utilities
join_dragons
: Worm and Dragon Functions
komaster_trymove
: Move Functions
liberty_of_string
: String Functions
location_to_string
: Print Utilities
make_domains
: Eye Functions
make_dragons
: Worm and Dragon Functions, Move Generation Basics
make_worms
: Worm and Dragon Functions, Move Generation Basics
marginal_eye_space
: Eye Functions
mark_string
: String Functions
maxterri
: Pattern Values
minterri
: Pattern Values
minvalue
: Pattern Values
modify_depth_values
: General Utilities
modify_eye_spaces1
: Connection Functions
move_in_stack
: Move Functions
move_reason_known
: Local MG Functions
neighbor_of_string
: String Functions
originate_eye
: Eye Functions
OTHER_COLOR
: Basic Data Structures
owl_attack
: Owl Functions, The Owl Code
owl_connection_defends
: Owl Functions
owl_defend
: Owl Functions, The Owl Code
owl_does_attack
: Owl Functions
owl_does_defend
: Owl Functions
owl_lively
: Owl Functions
owl_reasons
: Owl Functions, Move Generation Basics
owl_substantial
: Owl Functions
owl_threaten_attack
: Owl Functions
owl_threaten_defense
: Owl Functions
play_attack_defend2_n
: General Utilities
play_attack_defend_n
: General Utilities
play_break_through_n
: General Utilities
play_move
: Move Functions
popgo
: Move Functions, Roadmap
print_eye
: Eye Functions
propagate_worm
: Worm and Dragon Functions
proper_eye_space
: Eye Functions
propogate_eye
: Eye Functions
purge_persistent_reading_cache
: Persistent Cache
read_result_dump
: Hash Functions
READ_RETURN
: Hash Functions
READ_RETURN0
: Hash Functions
readsgffile
: SGF
remove_attack_move
: Move Generation Functions
remove_defense_move
: Move Generation Functions
remove_eyepoint
: Eye Functions
remove_half_eye
: Eye Functions
remove_lunch
: Move Generation Functions
remove_move_reason
: Local MG Functions
remove_opponent_attack_and_defense_moves
: Local MG Functions
remove_stone
: Board Setup Functions
reset_trymove_counter
: Move Functions
restore_depth_values
: General Utilities
review_move_reasons
: Move Generation Functions
revise_semeai
: Move Generation Basics
rr_get_pos_i
: Hash Functions
rr_get_pos_j
: Hash Functions
rr_get_routine
: Hash Functions
rr_get_stackp
: Hash Functions
safe_move
: Reading Basics
same_dragon
: General Utilities
same_string
: String Functions
same_worm
: General Utilities
search_persistent_reading_cache
: Persistent Cache
semeai
: Move Generation Basics
set_maximum_move_value
: Move Generation Functions
set_maximum_territorial_value
: Move Generation Functions
set_minimum_move_value
: Move Generation Functions
set_minimum_territorial_value
: Move Generation Functions
set_temporary_depth_values
: General Utilities
setup_board
: Board Setup Functions
sgf_write_header
: SGF
sgfAddChild
: SGF
sgfAddComment
: SGF
sgfAddPlay
: SGF
sgfAddPlayLast
: SGF
sgfAddProperty
: SGF
sgfAddPropertyFloat
: SGF
sgfAddPropertyInt
: SGF
sgfAddStone
: SGF
sgfBoardChar
: SGF
sgfBoardNumber
: SGF
sgfBoardText
: SGF
sgfCircle
: SGF
sgfCreateHeaderNode
: SGF
sgfGetCharProperty
: SGF
sgfGetFloatProperty
: SGF
sgfGetIntProperty
: SGF
sgfMark
: SGF
sgfMkProperty
: SGF
sgfNewNode
: SGF
sgfOverwriteProperty
: SGF
sgfOverwritePropertyFloat
: SGF
sgfOverwritePropertyInt
: SGF
sgfPrev
: SGF
sgfPrintCharProperty
: SGF
sgfPrintCommentProperty
: SGF
sgfRoot
: SGF
sgfSquare
: SGF
sgfStartVariant
: SGF
sgfStartVariantFirst
: SGF
sgftree_clear
: SGF
sgftree_readfile
: SGF
sgftreeAddComment
: SGF
sgftreeAddPlay
: SGF
sgftreeAddPlayLast
: SGF
sgftreeAddStone
: SGF
sgftreeBoardChar
: SGF
sgftreeBoardNumber
: SGF
sgftreeBoardText
: SGF
sgftreeCircle
: SGF
sgftreeCreateHeaderNode
: SGF
sgftreeMark
: SGF
sgftreeNodeCheck
: SGF
sgftreeSetLastNode
: SGF
sgftreeSquare
: SGF
sgftreeStartVariant
: SGF
sgftreeStartVariantFirst
: SGF
sgftreeTriangle
: SGF
sgftreeWriteResult
: SGF
sgfTriangle
: SGF
sgfWriteResult
: SGF
shape
: Pattern Values
shapes
: Move Generation Basics
shapes_callback
: Patterns Overview
show_dragons
: Worm and Dragon Functions
small_semeai
: Reading Basics
snapback
: Reading Basics
status_to_string
: Print Utilities
stones_on_board
: Status Functions
store_persistent_reading_cache
: Persistent Cache
strategically_sound_defense
: Local MG Functions
terri
: Pattern Values
topological_eye
: Eye Functions
TRACE
: Print Utilities
TRY_MOVE
: Move Functions
tryko
: Move Functions
trymove
: Move Functions, Roadmap
unconditional_life
: Worms
value
: Pattern Values
value_move_reasons
: Local MG Functions
value_moves
: Local MG Functions
vgprintf
: Print Utilities
vital_chain
: General Utilities, Owl Functions
writesgf
: SGF