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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.
GNU Go starts by trying to understand the current board position as good as possible. Using the information found in this first phase, and using additional move generators, a list of candidate moves is generated. Finally, each of the candidate moves is valued according to its territorial value (including captures or life-and-death effects), and possible strategical effects (such as strengthening a weak group).
Note that while GNU Go does, of course, do a lot of reading to analyze possible captures, life and death of groups etc., it does not (yet) have a fullboard lookahead.
4.1 Gathering Information | ||
4.2 Move Generators | Selecting Candidate Moves | |
4.3 Move Valuation | Selecting the best Move | |
4.4 Detailed Sequence of Events | Outline of genmove() .
| |
4.5 Roadmap | Description of the different files. | |
4.6 Coding styles and conventions | Coding conventions. | |
4.7 Navigating the Source |
This is by far the most important phase in the move generation. Misunderstanding life-and-death situations can cause gross mistakes. Wrong territory estimates will lead to inaccurate move valuations. Bad judgement of weaknesses of groups make strategic mistakes likely.
This information gathering is done by the function examine_position()
.
It first calls make_worms()
.
Its first steps are very simple: it identifies sets of directly connected stones, called worms, and notes their sizes and their number of liberties.
Soon after comes the most important step of the worm analysis: the tactical reading code (see section Tactical reading) is called for every worm. It tries to read out which worms can be captured directly, giving up as soon as a worm can reach 5 liberties. If a worm can be captured, the engine of course looks for moves defending against this capture. Also, a lot of effort is made to find virtually all moves that achieve the capture or defense of a worm.
After knowing which worms are tactically stable, we can make a first picture of the balance of power across the board: the Influence Function code is called for the first time.
This is to aid the next step, the analysis of dragons. By a dragon we mean a group of stones that cannot be disconnected.
Naturally the first step in the responsible function make_dragons()
is to identify these dragons, i.e. determine which worms cannot be
disconnected from each other. This is partly done by patterns, but
in most cases the specialized readconnect code
is called. This module does a minimax search to determine whether two
given worms can be connected with, resp. disconnected from each other.
Then we compute various measures to determine how strong or weak any given dragon is:
For those dragons that are considered weak, a life and death analysis is made (see section The Owl Code). If two dragons next to each other are found that are both not alive, we try to resolve this situation with the semeai module.
For a more detailed reference of the worm and dragon analysis (and explanations of the data structures used to store the information), see See section Worms and Dragons.
The influence code is then called second time to make a detailed analysis of likely territory. Of course, the life-and-death status of dragons are now taken into account.
The territorial results of the influence module get corrected by the break-in module. This specifically tries to analyze where an opponent could break into an alleged territory, with sequences that would be too difficult to see for the influence code.
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.
For a list and explanation of move reasons used in GNU Go, and how they are evaluated, see See section Move generation.
There are a couple of move generators that only extract data found in the previous phase, examining the position:
worm_reasons()
Moves that have been found to capture or defend a worm are proposed as candidates.
owl_reasons()
The status of every dragon, as it has been determined by the owl code (see section The Owl Code) in the previous phase, is reviewed. If the status is critical, the killing or defending move gets a corresponding move reason.
semeai_move_reasons()
Similarly as
owl_reasons
, this function proposes moves relevant for semeais.
break_in_move_reasons()
This suggests moves that have been found to break into opponent's territory by the break-in module.
The following move generators do additional work:
fuseki()
Generate a move in the early fuseki, either in an empty corner of from the fuseki database.
shapes()
This is probably the most important move generator. It finds patterns from ‘patterns/patterns.db’, ‘patterns/patterns2.db’, ‘patterns/fuseki.db’, and the joseki files 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 (in ‘patterns/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 section The Pattern Code, for a complete documentation of patterns.)
combinations()
See if there are any combination threats or atari sequences and either propose them or defend against them.
revise_thrashing_dragon()
This module does not directly propose move: If we are clearly ahead, and the last move played by the opponent is part of a dead dragon, we want to attack that dragon again to be on the safe side. This is done be setting the status of this thrashing dragon to unkown and repeating the shape move generation and move valution.
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 from
DEAD
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, each proposed candidate
move goes through a detailed valuation by the function
review_move_reasons
. This invokes some analysis to try to turn
up other move reasons that may have been missed.
The most important value of a move is its territorial effect. see section Influence and Territory explains in detail how this is determined.
This value is modified for all move reasons that cannot be expressed directly in terms of territory, such as combination attacks (where it is not clear which of several strings will get captured), strategical effects, connection moves, etc. A large set heuristics is necessary here, e.g. to avoid duplication of such values. This is explained in more detail in Valuation of suggested moves.
First comes the sequence of events when
examine_position()
is run from genmove()
. This
is for reference only.
|
Now a summary of the sequence of events during the
move generation and selection phases of genmove()
, which
take place after the information gathering phase has been completed:
|
The GNU Go engine is contained in two directories, ‘engine/’ and ‘patterns/’. Code related to the user interface, reading and writing of Smart Game Format files, and testing are found in the directories ‘interface/’, ‘sgf/’, and ‘regression/’. Code borrowed from other GNU programs is contained in ‘utils/’. That directory also includes some code developed within GNU Go which is not go specific. 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:
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.
This contains
main()
. The ‘gnugo’ target is thus built in the ‘interface/’ directory.
In ‘engine/’ there are the following files:
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.
This file contains code for the maintenance of the board. For example it contains the important function
trymove()
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.
Code to detect moves which can break into supposed territory and moves to prevent this.
As a means of speeding up reading, computed results are cached so that they can be quickly reused if the same position is encountered through e.g. another move ordering. This is implemented using a hash table.
Clock code, including code allowing GNU Go to automatically adjust its level in order to avoid losing on time in tournaments.
When something can (only) be captured through a series of ataris or other threats we call this a combination attack. This file contains code to find such attacks and moves to prevent them.
This contains
make_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.
Code to find certain types of endgame moves.
Code to force filling of dame (backfilling if necessary) at the end of the game.
Generates fuseki (opening) moves from a database. Also generates moves in empty corners.
This file contains
genmove()
and its supporting routines, particularlyexamine_position()
.
This contains the principal global variables used by GNU Go.
This file contains declarations forming the public interface to the engine.
Hashing code implementing Zobrist hashing. (see section Hashing of Positions) The code in ‘hash.c’ provides a way to hash board positions into compact descriptions which can be efficiently compared. The caching code in ‘cache.c’ makes use of the board hashes when storing and retrieving read results.
This code determines which regions of the board are under the influence of either player. (see section Influence Function)
Header file for the engine. The name “liberty” connotes freedom (see section Copying).
This file contains the pattern matcher
matchpat()
, which looks for patterns at a particular board location. The actual patterns are in the ‘patterns/’ directory. The functionmatchpat()
is called by every module which does pattern matching, notablyshapes
.
Code for keeping track of move reasons.
Supporting code for lists of moves.
This file contains the code to recognize eye shapes, documented in See section Eyes and Half Eyes.
Code to fork off a second GNU Go process which can be used to simulate reading with top level information (e.g. dragon partitioning) available.
This file does life and death reading. Move generation is pattern based and the code in ‘optics.c’ is used to evaluate the eyespaces for vital moves and independent life. A dragon can also live by successfully escaping. Semeai reading along the same principles is also implemented in this file.
Persistent cache which allows reuse of read results at a later move or with additional stones outside an active area, which are those intersections thought to affect the read result.
Print utilities.
This file contains code to determine whether two strings can be connected or disconnected.
This file contains code to determine whether any given string can be attacked or defended. See section Tactical reading, for details.
This file contains
semeai()
, the module which detects dragons in semeai. To determine the semeai results the semeai reading in ‘owl.c’ is used.
Code to generate sgf traces for various types of reading.
This file contains
shapes()
, the module called bygenmove()
which tries to find moves which match a pattern (see section The Pattern Code).
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.
Code to determine whether a dragon is surrounded and to find moves to surround with or break out with.
An assortment of utilities, described in greater detail below.
This file contains the code which assigns values to every move after all the move reasons are generated. It also tries to generate certain kinds of additional move reasons.
This file contains
make_worms()
, code which is run at the beginning of each move cycle, before the code in ‘dragon.c’, to determine the attributes of every string. These attributes are things like liberties, wether the string can be captured (and how), etc
The directory ‘patterns/’ contains files related to pattern matching. Currently there are several types of patterns. A partial list:
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 Game Format.
Database of connection patterns.
Automatically generated file, containing connection patterns in form of struct arrays, compiled by
mkpat
from ‘conn.db’.
Automatically generated file, containing eyeshape patterns in form of struct arrays, compiled by
mkpat
from ‘eyes.db’.
Header file for ‘eyes.c’.
Database of eyeshape patterns. See section Eyes and Half Eyes, for details.
These are helper functions to assist in evaluating moves by matchpat.
Smart Game Format file containing 4-4 point openings
Automatically generated database of 4-4 point opening patterns, make by compiling ‘hoshi.sgf’
Joseki compiler, which takes a joseki file in Smart Game Format, and produces a pattern database.
Smart Game Format file containing 3-4 point openings
Automatically generated database of 3-4 point opening patterns, make by compiling ‘komoku.sgf’
Pattern compiler for the eyeshape databases. This program takes ‘eyes.db’ as input and produces ‘eyes.c’ as output.
Pattern compiler for the move generation and connection databases. Takes the file ‘patterns.db’ together with the autogenerated Joseki pattern files ‘hoshi.db’, ‘komoku.db’, ‘sansan.db’, ‘mokuhadzushi.db’, ‘takamoku.db’ and produces ‘patterns.c’, or takes ‘conn.db’ and produces ‘conn.c’.
Smart Game Format file containing 5-3 point openings
Pattern database compiled from mokuhadzushi.sgf
Smart Game Format file containing 3-3 point openings
Pattern database compiled from ‘sansan.sgf’
Smart Game Format file containing 5-4 point openings
Pattern database compiled from takamoku.sgf.
Pattern data, compiled from patterns.db by mkpat.
Header file relating to the pattern databases.
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.
As a workaround,
%o
at the beginning of the: format string suppresses the indentation.
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, ...)
:
While
TRACE
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 in ‘engine/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-3.6/’ and execute the command:
find . -print|grep "\.[ch]$" | xargs etags |
This will build a file called ‘gnugo-3.6/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-3.6/TAGS’, and henceforth you will be able to find any function with a minimum of keystrokes.
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