Optimizing Selective Search in Chess

Details Optimizing Selective Search in Chess Optimizing Selective Search in Chess

2010-09-02

arxiv.org/abs/1009.0550v1

Proceedings of the International Conference on Machine Learning (ICML) Workshop on Machine Learning and Games, Haifa, Israel,

Computer Science

Artificial Intelligence

Scientific paper

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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