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| About site: Artificial Intelligence/Games - Logistello |
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| About site: http://www.cs.ualberta.ca/~mburo/log.html |
Title: Artificial Intelligence/Games - Logistello Othello program written by Michael Buro. Publications, game records.
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LOGISTELLO's Homepage LOGISTELLO is one of today's strongest Othello programs. Besides the powerfulhardware on which it is running and the efficient implementation ofstandard game-tree searching techniques, the program's considerableplaying strength is mainly due to several new approaches for theconstruction of evaluation features, their combination, selectivesearch, and learning from previous games which I have investigated in my Ph.D. thesis and considerably improvedwhile working at NECI.Download Logistello's book skeleton (i.e. (self-)played games) for studying openings, trainingevaluation parameters, or just improving your bot's book. Games arestored as ASCII move sequences annotated with the final game result inblack's view. All ~37K lines are at least 24-ply WLD correct. The fileis gzip'ed. Click here if you prefer the WTHOR format.Logistello's source code is now available. Last update: November/4/2002: Stephane Nicolet found a bug in the MPC code - fixed.Logistello's X-window GUI source code.README file:This is the Logistello source directory which is licensed under theGPL. I worked on it from 1992 till 1998. As a result, it's not apretty sight: a zillion tools for handling different game fileformats, computing statistics, solving logistic and linear regressionsystems, book learning, running tournaments etc. Many of them are nowobsolete. Some of the code is hard to read - some comments andvariable names are even in German (Brett=board,Zug=move,Wert=value).I hardly can tell which file is actually used anymore. The makefilescan be a starting point for exploring the source code. The currentLogistello version is generated by "make ../oplayl". I have notincluded the training data, nor the opening book, nor the patternand Multi-ProbCut tables. Although the program compiles, it cannot beused to play Othello out of the box. All the software for creatingmissing tables is included, however. What's missing is the 17 milliontraining positions - which are not that hard to generate nowadays.The purpose of this release is to present the implementation detailsof a strong game-playing program. My hope is that it is useful fordesigning coming generations of even stronger programs.- Michael Buro, November 2002. Program overview Evaluation featuresgame stage dependent tables for each of the following patterns:horizontals/verticals of length 8diagonals of length 4-83x3 corner2x5 corneredge+2X a simple parity measureFeature combinationlinearSearchNegaScout with corner quiescence search and multi-ProbCutiterative deepeningMove sortinghash-table containing moves and value bounds (2**21 entries à 8 bytes)response killer listsshallow searchesSearch speed (on a Pentium-Pro 200 (1997), on today's hardware much faster)middle-game: ~160,000 nodes/secendgame: ~480,000 nodes/secSearch depth (in a 2x30 minutes game)middle-game: 18-23 selective including 10-15 brute-force plyendgame: win/loss/draw determination at 26-22 empty squares, exact score 1-2 ply laterOpening bookconsists for the moment of ca. 23k games and evaluations of "best" move alternativesis automatically updatedcurrently several machines are working all day long on book improvementMiscellanythinking on opponent's timecommunication with IOS via socket or with graphical interface via file systemOS / Language / CompilerUnix / C / gcc 2.7.2.1 Development History 1991: first experiments with statistical feature combination 1992: searching for significant and fast evaluation features 1993: here they are: estimated pattern tables, line approximation of mobility and potential mobility; features are combined using logistic regression; L wins its first tournament ("Paderborn I") achieving 16k nodes/sec in middle-game on a SPARC-10/M20. 1994: found an effective selective search approach: ProbCut; learning opening book 1995: 10-disc patterns; new book algo. which maximizes out-of-book evaluation 1996: multi-ProbCut; hashtable improvement 1997: new evaluation function based on plain linear regression; search speed is now 280K nodes/sec in middle-game on a DEC Alpha/500. Recent Improvements Mar 1995: 10-disc patterns May 1995: new best-first style endgame search for solving close positions faster Jul 1995: book-algorithm is now playing for maximal score when leaving the book May 1996: book-randomization Oct 1996: multi-ProbCut Nov 1996: major table estimation bug fixed, new version beats old 57% of the time Dec 1996: hash-table improvement saves 15-40% searchtime Mar 1997: a new table estimation technique increases the playing strength considerably Apr 1997: the entire book has been re-computed using the new evaluation function May 1997: speed boost on a DEC Alpha/500: in middle-game 280k nodes/sec, in endgame 1000k nodes/sec July 1997: increasing the number of training examples by means of book correction and generating rare positions to fill table gaps improves the evaluation functionTournament Results (last updated: January/28/98) Murakami vs. Logistello & Workshop on Game-Tree Search (last update: August/20/97 Match Report!) Princeton I: Logistello wins 22 games in a rowlast modified on ; you are visitor # since Dec/18/1995to homepage of LOG's creator |
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Othello | program | written | by | Michael | Buro. | | Publications, | game | records. |
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http://www.cs.ualberta.ca/~mburo/log.html
Logistello 2008 October
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Othello program written by Michael Buro. Publications, game records.
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