1,044 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

    Get PDF
    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

    Reference fallible endgame play

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    A reference model of fallible endgame play is defined in terms of a spectrum of endgame players whose play ranges in competence from the optimal to the anti-optimal choice of move. They may be used as suitably skilled practice partners, to assess a player, to differentiate between otherwise equi-optimal moves, to promote or expedite a game result, to run Monte-Carlo simulations, and to identify the difficulty of a position or a whole endgame

    Soar Checkers - An Intelligent Checkers Playing Agent in Soar

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    The classic board game of checkers is ideally suited for research in AI game-playing programs or agents. The objective behind Soar Checkers is to investigate if it is possible to create an agent-based game playing system that would beat novices with ease and at least challenge advanced novice to intermediate-level players by designing a rules-based expert system whose knowledge base consists of nothing more than the rules of checkers, and a set of guidelines for game-play based on good strategy. Soar was chosen as the platform for building this agent because it came built-in with features that facilitate creating rules-based expert systems, has been proven to be fairly reliable in developing such systems (including flight simulators) for over twenty years and makes it relatively straight-forward to have multiple agents play each other, and to add or modify features or strategies to the agents. Though the problem definition makes it inherently hard to objectively quantify the results, the objectives were successfully achieved for the most part. It was also seen that all other things being equal, the player going second ( White ) has a built-in advantage, thereby confirming a widely held belief among the checkers community
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