Title: A methodology for learning players' styles from game records
Authors: Mark Levene; Trevor Fenner
Addresses: Department of Computer Science and Information Systems, Birkbeck College, University of London, London WC1E 7HX, UK. ' Department of Computer Science and Information Systems, Birkbeck College, University of London, London WC1E 7HX, UK
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.
Keywords: temporal difference learning; evaluation function; game records; player styles; computer chess; chess players; game playing; gaming; playing styles.
DOI: 10.1504/IJAISC.2011.042711
International Journal of Artificial Intelligence and Soft Computing, 2011 Vol.2 No.4, pp.272 - 286
Received: 10 Jan 2011
Accepted: 12 Feb 2011
Published online: 31 Mar 2015 *