Abstract
In action games, the computer's behavior lacks diversity and human players are able to learn how the computer behaves by playing the same game over and over again. As a result, human players eventually grow tired of the game. Therefore, this paper proposes a method of imitating the behavior of human players by creating profiles of players from their play data. By imitating what many different players do, a greater variety of actions can be created. © IFIP International Federation for Information Processing 2006.
Cite
CITATION STYLE
Nakano, A., Tanaka, A., & Hoshino, J. (2006). Imitating the behavior of human players in action games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4161 LNCS, pp. 332–335). Springer Verlag. https://doi.org/10.1007/11872320_44
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