A methodology for learning players' styles from game records Online publication date: Tue, 31-Mar-2015
by Mark Levene; Trevor Fenner
International Journal of Artificial Intelligence and Soft Computing (IJAISC), Vol. 2, No. 4, 2011
Abstract: We describe a preliminary investigation into learning a Chess player's style from game records. The method is based on attempting to learn features of a player's individual evaluation function using the method of temporal differences, with the aid of a conventional Chess engine architecture. Some encouraging results were obtained in learning the styles of two Chess world champions, and we report on our attempt to use the learnt styles to discriminate between the players from game records, by trying to detect who was playing white and who was playing black. We also discuss some limitations of our approach.
Online publication date: Tue, 31-Mar-2015
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