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Optimizing Selective Search in Chess

Published 2 Sep 2010 in cs.AI and cs.NE | (1009.0550v1)

Abstract: 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.

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