Tank War Using Online Reinforcement Learning

Real-Time Strategy(RTS) games provide a challenging platform to implement online reinforcement learning(RL) techniques in a real application. Computer as one player monitors opponents'(human or other computers) strategies and then updates its own policy using RL methods. In this paper, we propo...

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Veröffentlicht in:	Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 Jg. 2; S. 497 - 500
Hauptverfasser:	Andersen, Kresten Toftgaard, Zeng, Yifeng, Christensen, Dennis Dahl, Tran, Dung
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	Washington, DC, USA IEEE Computer Society 15.09.2009 IEEE
Schriftenreihe:	ACM Conferences
Schlagworte:	Application software Cities and towns Computer applications Computer science Computing methodologies > Artificial intelligence > Control methods Computing methodologies > Artificial intelligence > Search methodologies Computing methodologies > Machine learning Computing methodologies > Modeling and simulation > Model development and analysis > Modeling methodologies Conferences Humans Intelligent agent Learning Real-Time Strategy Game Reinforcement Learning State-space methods Testing Theory of computation > Design and analysis of algorithms > Algorithm design techniques > Dynamic programming Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms Theory of computation > Models of computation > Interactive computation Theory of computation > Theory and algorithms for application domains > Machine learning theory > Online learning theory Real-Time Strategy Game Reinforcement Learning
ISBN:	0769538010, 9780769538013
Online-Zugang:	Volltext
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