134 research outputs found

    Space-efficient indexing of endgame tables for chess

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    Chess endgame tables should provide efficiently the value and depth of any required position during play. The indexing of an endgame’s positions is crucial to meeting this objective. This paper updates Heinz’ previous review of approaches to indexing and describes the latest approach by the first and third authors. Heinz’ and Nalimov’s endgame tables (EGTs) encompass the en passant rule and have the most compact index schemes to date. Nalimov’s EGTs, to the Distance-to-Mate (DTM) metric, require only 30.6 × 109 elements in total for all the 3-to-5-man endgames and are individually more compact than previous tables. His new index scheme has proved itself while generating the tables and in the 1999 World Computer Chess Championship where many of the top programs used the new suite of EGTs

    Space-efficient Indexing of Chess Endgame Tables

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    Chess endgame tables should provide efficiently the value and depth of any required position during play. The indexing of an endgame’s positions is crucial to meeting this objective. This paper updates Heinz’ previous review of approaches to indexing and describes the latest approach by the first and third authors. Heinz’ and Nalimov’s endgame tables (EGTs) encompass the en passant rule and have the most compact index schemes to date. Nalimov’s EGTs, to the Distance-to-Mate (DTM) metric, require only 30.6 × 10^9 elements in total for all the 3-to-5-man endgames and are individually more compact than previous tables. His new index scheme has proved itself while generating the tables and in the 1999 World Computer Chess Championship where many of the top programs used the new suite of EGTs

    Computer Chess: From Idea to DeepMind

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    Computer chess has stimulated human imagination over some two hundred and fifty years. In 1769 Baron Wolfgang von Kempelen promised Empress Maria Theresia in public: “I will invent a machine for a more compelling spectacle [than the magnetism tricks by Pelletier] within half a year.” The idea of an intelligent chess machine was born. In 1770 the first demonstration was given.The real development of artificial intelligence (AI) began in 1950 and contains many well-known names, such as Turing and Shannon. One of the first AI research areas was chess. In 1997, a high point was to be reported: world champion Gary Kasparov had been defeated by Deep Blue. The techniques used included searching, knowledge representation, parallelism, and distributed systems. Adaptivity, machine learning and the recently developed deep learning mechanism were only later on added to the computer chess research techniques.The major breakthrough for games in general (including chess) took place in 2017 when (1) the AlphaGo Zero program defeated the world championship program AlphaGo by 100-0 and (2) the technique of deep learning also proved applicable to chess. In the autumn of 2017, the Stockfish program was beaten by AlphaZero by 28-0 (with 72 draws, resulting in a 64-36 victory). However, the end of the disruptive advance is not yet in reach. In fact, we have just started. The next milestone will be to determine the theoretical game value of chess (won, draw, or lost). This achievement will certainly be followed by other surprising developments.Algorithms and the Foundations of Software technolog

    The History of Computer Games

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    This handout presents milestones in the history of computer backgammon, computer bridge, computer checkers, computer chess, computer Go, computer Othello, and computer poker

    The Cord Weekly (February 21, 1991)

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    The Johnsonian February 29, 1988

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    The Johnsonian is the weekly student newspaper of Winthrop University. It is published during fall and spring semesters with the exception of university holidays and exam periods. We have proudly served the Winthrop and Rock Hill community since 1923.https://digitalcommons.winthrop.edu/thejohnsonian1980s/1187/thumbnail.jp
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