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1995
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3 pages
1 file
This short paper defines the terminology used to support computer chess work, and introduces the basic concpets behind chess programs. It is intended to be of general interest, providing background information ot new ideas.
INFOR: Information Systems and Operational Research, 1973
The purpose of this paper is to discuss ideas used in current chess playing programs. A short history of events leading to the present state of the art is given and a survey made of present day programs. The Newell, Shaw, and Simon program of 1958 is included since it embodies useful ideas that other programs appear not to employ. The possible performance limits for current techniques will be considered, including reasons for these beliefs. A summary of the major ideas contained in these programs is then presented and suggestions made for the improvement and development of future chess-playing programs. RESUME Le but de cet article est de discuter certaines iddes utilisdes dans les programmes pour le jeu d'echecs. On pr&ente un bref historique des ^vfenements qui ont abouti a l'dtat actuel. On fait la revue des programmes actuels. Le programme de Newell, Shaw, et Simon, ^crit en 1958, est inclus. En effet, il incorpore certaines id^es utiles qui ne semblent pas Stre encore exploit^es dans les programmes actuels. Les limitations des mdthodes courantes ainsi que leurs causes sont considdr^es. Finalement, on resume les id^es principales contenues dans ces programmes et on pr^sente des suggestions pour l'am^lioration et le d^veloppement des programmes qui jouent aux dchecs.
berkantakin.com
This paper describes a computer program, which is able to play chess. The program performs three main tasks as in all chess-playing computer programs; board representation, a search algorithm, and an evaluation function. Board representation shows the placement of the pieces on a graphical user interface (GUI), and handles the moves of the pieces to comply with the rules of chess. The search algorithm runs minimax algorithm based on α α α α-β β β β pruning with move ordering heuristics before selecting the next move, and the next move is decided according to the result of the evaluation function.
2000
Article prepared for the ENCYCLOPEDIAOF ARTIFICIAL INTELLIGENCE, S. Shapiro (editor), D. Eckroth (Managing Editor) to be published by John Wiley, 1987.
ICGA Journal, 1993
We describe a suite of 5500 test positions for testing chess playing programs. They are available as pub/wds/ChessTest.tar.Z by anonymous ftp to external.NJ.NEC.COM. Almost all of these positions are unoriginal and were obtained by scanning in diagrams from chessbooks with an optical scanner. Gnuchess 4.0, at one minute per move on a 50 MHz MIPS R4000, scores 16-71% on our test les. We describe the software we wrote to accomplish the scanning task. If you take the test, please send us
Proceedings of the ACM '81 conference on - ACM 81, 1981
Two papers will be presented and a general discussion period will then follow. The panel members are all members of the ACM Computer Chess Committee. The first paper, which appears elsewhere in the Proceedings, is the work of Tony Marsland. It is entitled “A survey of enhancements to the alpha-beta algorithm.” The paper reviews move ordering and search reduction techniques
Lecture Notes in Computer Science, 2015
We present the design of a computer program for playing Progressive Chess. In this game, rather than just making one move per turn, players play progressively longer series of moves. Our program follows the generally recommended strategy for this game, which consists of three phases: looking for possibilities to checkmate the opponent, playing generally good moves when no checkmate can be found, and preventing checkmates from the opponent. In this paper, we focus on efficiently searching for checkmates, putting to test various heuristics for guiding the search. We also present the findings of self-play experiments between different versions of the program.
Theoretical Computer Science, 2016
In Progressive chess, rather than just making one move per turn, players play progressively longer series of moves. Combinatorial complexity generated by many sequential moves represents a difficult challenge for classic search algorithms. In this article, we present the design of a state-of-the-art program for Progressive chess. The program follows the generally recommended strategy for this game, which consists of three phases: looking for possibilities to checkmate the opponent, playing sequences of generally good moves when checkmate is not available, and preventing checkmates from the opponent. For efficient and effective checkmate search we considered two versions of the A* algorithm, and developed five different heuristics for guiding the search. For finding promising sequences of moves we developed another set of heuristics, and combined the A* algorithm with minimax search, in order to fight the combinatorial complexity. We constructed an opening book, and designed specialized heuristics for playing Progressive chess endgames. An application with a graphical user interface was implemented in order to enable human players to play Progressive chess against the computer, and to use the computer to analyze their games. The program performed excellently in experiments with checkmate search, and won both mini-matches against a human chess master. We also present the findings of self-play experiments between different versions of the program.
Type 1- Project: Students have implemented International Chess Project. The outputs will be: Code with Demo, Report (see a sample), Slides for Presentation.
ICGA Journal, 2002
L'auteur a accordé une licence non exclusive permettant à la Bibliothèque nationale du Canada de reproduire, prêter, distribuer ou vendre des copies de cette thèse sous la forme de microfiche/film, de reproduction sur papier ou sur format électronique. L'auteur conserve la propriété du droit d'auteur qui protège cette thèse. Ni la thèse ni des extraits substantiels de celle-ci ne doivent être imprimés ou aturement reproduits sans son autorisation. l would like to thank my supervisor Zeljko Zilic. His guidance and patience has been greatly appreciated during my two years at McGill. He is always willing to review papers and to send his students to numerous conferences. He is partieularly adept at suggesting relevant and interesting research topies as well as accepting students' ideas. For these and many more reasons, l do not hesitate to spend the next three years as a student of his. Monty Newborn has graciously accepted to co-supervise this work. His knowledge in computer chess is well documented and l thank him for participating in my project. M. Newborn will also be an indispensable advisor for my up-coming doctorate in hardware-accelerated automated theorem proving. An unexpected contribution to my project was made by a recent acquaintance from www.talkchess.com.Keith Evans has spent numerous hours reading my work and sharing his thoughts through many email discussions. l would also like to thank the Natural Sciences and Engineering Research Council of Canada for the financial support. This has allowed me to select a research topic regardless of financial or commercial implications. J'aimerais remercier André St-Amand pour son aide lors de la recherche bibliographique. C'est grâce à lui et les nombreuses discussions sur la programmation des échecs que j'ai choisi ce suj et de maîtrise. Ses nombreuses analyses de parties démontrant les faiblesses de mon programme ont été une source de motivation indispensable. J'aimerais également remercier Normand Leclerc d'avoir créé les images des piecès et de l'échiquier qui ont servi à l'interface graphique de MBCHESS. Merci à Patrick Cardinal pour son aide avec Jb.TEX et à André Boulé pour m'avoir suggéré d'utiliser les "named pipe" .
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