Comparing PSO structures to learn the game of checkers from zero knowledge

This paper investigates the effectiveness of various particle swarm optimiser structures to learn how to play the game of checkers. Co-evolutionary techniques are used to train the game playing agents. Performance is compared against a player making moves at random. Initial experimental results indicate definite advantages in using certain information sharing structures and swarm size configurations to successfully learn the game of checkers.