Most modern real-time strategy computer games have a sophisticated but fixed 'AI' component that controls the computer's actions. Once the user has learned how such a game will react, the game quickly loses its appeal. This paper describes an example of how a learning classifier system (based on Wilson's ZCS [1]) can be used to equip the computer with dynamically-changing strategies that respond to the user's strategies, thus greatly extending the games playability for serious gamers.
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