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.
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References
Schwab, B.: AI Game Engine Programming, pp. 203–210. Charles River Media, Hingham (2004)
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© 2006 IFIP International Federation for Information Processing
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Nakano, A., Tanaka, A., Hoshino, J. (2006). Imitating the Behavior of Human Players in Action Games. In: Harper, R., Rauterberg, M., Combetto, M. (eds) Entertainment Computing - ICEC 2006. ICEC 2006. Lecture Notes in Computer Science, vol 4161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11872320_44
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DOI: https://doi.org/10.1007/11872320_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45259-1
Online ISBN: 978-3-540-45261-4
eBook Packages: Computer ScienceComputer Science (R0)