Dynamic Strategies in a Real-Time Strategy Game

Abstract. 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. 1 The Game and the Classifier System Real-time strategy (RTS) games typically involve fighting a battle against a computer opponent. This opponent typically has a very sophisticated but essentially static strategy and once the user has learned how it behaves, the game loses its playability. To get round this limitation we have used a learning classifier system (LCS) to provide the computer with the capability to dynamically change its strategy. LCSs are sometimes criticized for be...

• Type: Conference
• Year: 2003
• Where: GECCO
• Authors: William Joseph Falke II, Peter Ross
• Keywords: Computer, Game, GECCO 2003, Real-time Strategy