Evolving FPS Game Players by Using Continuous EDA-RL
A1211.pdf 226 KB
This paper extends EDA-RL, Estimation of Distribution Algorithms for Reinforcement Learning Problems, to continuous domain. The extended EDA-RL is used to constitiute FPS game players. In order to cope with continuous input-output relations, Gaussian Network is employed as in EBNA. Simulation results on Unreal Tournament 2004, one of major FPS games, confirm the effectiveness of the proposed method.
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
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IEEE SMC Hiroshima Chapter
(c) Copyright by IEEE SMC Hiroshima Chapter.
Graduate School of Engineering
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