Learning Control of Search Extensions.
Yngvi Björnsson, T.A. Marsland · 2002
The strength of a program for playing an adversary game like chess or checkers is greatly influenced by how selectively it explores the various branches of the game tree. Typically, some branch paths are discontinued early while others are explored more deeply. Finding the best set of parameters to control these extensions is a difficult, time consuming, and tedious task. In this paper we describe a method for automatically tuning searchextension parameters in adversary search. One of the main appeals of the method is that it is non-intrusive and domain independent. Therefore, with only minimal modifications, almost any search-based game-playing program can be “plugged ” into the learning module. Experimental results are provided in the domain of chess. 1