  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.
