n South African Computer Journal - Evolving intelligent game-playing agents : research article




Traditional game playing programs have relied on advanced search algorithms and hand-tuned evaluation functions to play 'intelligently'. A historical overview of these techniques is provided, followed by a revealing look at recent developments in coevolutionary strategies to facilitate game learning. The use of particle swarms in conjunction with neural networks to learn how to play tic-tac-toe is experimentally compared to current game learning research. The use of a new particle swarm neighbourhood structure and innovative board state representation show promising results that warrant further investigation to its application in more complex games like checkers.


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