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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Schwab, B.: AI Game Engine Programming, pp. 203–210. Charles River Media, Hingham (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 IFIP International Federation for Information Processing
About this paper
Cite this paper
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
Download citation
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)