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Genetically programmed strategies for chess endgame

机译:国际象棋残局的基因编程策略

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Classical chess engines exhaustively explore moving possibilities from a chessboard configuration to choose what the next best move to play is. In this article we present a new method to solve chess endgames without using Brute-Force algorithms or endgame tables. We are proposing to use Genetic Programming to combine elementary chess patterns defined by a chess expert. We apply this method specifically to the classical King-Rook-King endgame. We show that computed strategies are both effective and generic for they manage to win against several opponents (human players and artificial ones such as the chess engine CRAFTY). Besides, the method allows to propose strategies that are clearly readable and useable for a purpose such as teaching chess.
机译:经典的国际象棋引擎详尽地探索了棋盘配置中的移动可能性,以选择下一个最佳棋子。在本文中,我们提出了一种无需使用蛮力算法或残局表即可解决国际象棋残局的新方法。我们建议使用遗传编程来组合国际象棋专家定义的基本国际象棋模式。我们将这种方法专门应用于经典的King-Rook-King残局。我们证明了计算策略既有效又通用,因为它们设法与几个对手(人类玩家和象棋引擎CRAFTY等人为对手)取得胜利。此外,该方法允许提出清晰可读且可用于诸如国际象棋之类的目的的策略。

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