Computer chess move-ordering schemes using move influence

Kieran Greer

doi:10.1016/S0004-3702(00)00026-6

Computer chess move-ordering schemes using move influence

2000-07-01

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Kieran Greer *

DOI：10.1016/S0004-3702(00)00026-6

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The chessmaps heuristic is a pattern-oriented approach to ordering moves for the game of chess. It uses a neural network to learn a relation between the control of the squares and the influence of a move. Depending on what squares a player controls, the chessmaps heuristic tries to determine where the important areas of the chessboard are. Moves that influence these important areas are then ordered first. The heuristic has been incorporated into a move-ordering algorithm that also takes account of immediate tactical threats. Human players also rely strongly on patterns when selecting moves, but would also consider immediate tactical threats, so this move-ordering algorithm is an attempt to mimic something of the human thought process when selecting a move. This paper presents a new definition for the influence of a move, which improves the performance of the heuristic. It also presents a new experience-based approach to determining what areas of the chessboard are important, which may actually be preferred to the chessmaps heuristic. The results from game-tree searches suggest that the move-ordering algorithm could compete with the current best alternative of using the history heuristic with capture moves in a brute-force search. (C) 2000 Elsevier Science B.V. All rights reserved.

Keywords:

chessmaps heuristic

computer chess

search heuristic

pattern-oriented

neural network

Computer chess move-ordering schemes using move influence

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