Optimizing Selective Search in Chess

09/02/2010

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by   Omid David-Tabibi, et al.

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In this paper we introduce a novel method for automatically tuning the search parameters of a chess program using genetic algorithms. Our results show that a large set of parameter values can be learned automatically, such that the resulting performance is comparable with that of manually tuned parameters of top tournament-playing chess programs.