Descripción
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A grammar-guided genetic program is presented to automatically build and evolve populations of AI controlled enemies in a 2D third-person shooter called Genes of War. This evolutionary system constantly adapts enemy behaviour, encoded by a multi-layered fuzzy control system, while the game is being played. Thus the enemy behaviour fits a target challenge level for the purpose of maximizing player satisfaction. Two different methods to calculate this challenge level are presented: ?hardwired? that allows the desired difficulty level to be programed at every stage of the gameplay, and ?adaptive? that automatically determines difficulty by analyzing several features extracted from the player's gameplay. Results show that the genetic program successfully adapts armies of ten enemies to different kinds of players and difficulty distributions. | |
Internacional
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Si |
Nombre congreso
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EVOSTAR 2012 |
Tipo de participación
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960 |
Lugar del congreso
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Málaga |
Revisores
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Si |
ISBN o ISSN
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978-3-642-29177-7 |
DOI
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Fecha inicio congreso
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11/04/2012 |
Fecha fin congreso
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13/04/2012 |
Desde la página
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204 |
Hasta la página
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213 |
Título de las actas
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Applications of Evolutionary Computation |