Statistical Feature Combination for the Evaluation of Game Positions

This article describes an application of three well{known statistical methods in the eld of game{tree search: using a large number of classi ed Othello positions, feature weights for evaluation functions with a game{phase{independent meaning are estimated by means of logistic regression, Fisher's linear discriminant, and the quadratic discriminant function for normally distributed features. Thereafter, the playing strengths are compared by means of tournaments between the resulting versions of a world{class Othello program. In this application, logistic regression | which is used here for the rst time in the context of game playing | leads to better results than the other approaches.