このエントリーをはてなブックマークに追加
ID 19659
Eprint ID
19659
FullText URL
Author
Tsubota Hajime
Abstract
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.
Published Date
2009-11-12
Publication Title
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
Volume
volume2009
Issue
issue1
Publisher
IEEE SMC Hiroshima Chapter
Start Page
143
End Page
146
ISSN
1883-3977
NCID
BB00577064
Content Type
Conference Paper
language
英語
Copyright Holders
IEEE SMC Hiroshima Chapter
Event Title
5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
Event Location
東広島市
Event Location Alternative
Higashi-Hiroshima City
File Version
publisher
Refereed
True
Eprints Journal Name
IWCIA