This paper investigates the use of n-tuple systems as position value functions for the game of Othello. The architecture is described, and then evaluated for use with temporal difference learning. Performance is compared with previously developed weighted piece counters and multi-layer perceptrons. The n-tuple system is able to defeat the best performing of these after just five hundred games o...

An approach to develop new game playing strategies based on arti cial evolution of neural networks is presented. Evolution was directed to discover strategies in Othello against a random-moving opponent and later against an search program. The networks discovered rst a standard positional strategy, and subsequently a mobility strategy, an advanced strategy rarely seen outside of tournaments. Th...