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Volumn 37, Issue 9, 2006, Pages 22-31

Multiagent reinforcement learning with the partly high-dimensional state space

Author keywords

Modular Q learning; Multiagent; Reinforcement learning; State space

Indexed keywords

DATA STORAGE EQUIPMENT; INTELLIGENT AGENTS; MULTI AGENT SYSTEMS; PERFORMANCE; STATE SPACE METHODS;

EID: 33746156507     PISSN: 08821666     EISSN: 1520684X     Source Type: Journal    
DOI: 10.1002/scj.20526     Document Type: Article
Times cited : (4)

References (14)
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    • 33746162804 scopus 로고    scopus 로고
    • State space construction for cooperative behavior acquisition in the environments including multiple learning robots
    • Uchibe E, Asada M, Hosoda K. State space construction for cooperative behavior acquisition in the environments including multiple learning robots. J Robot Soc Japan 2002;20:281-289.
    • (2002) J Robot Soc Japan , vol.20 , pp. 281-289
    • Uchibe, E.1    Asada, M.2    Hosoda, K.3
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    • 33746129207 scopus 로고    scopus 로고
    • State-action space construction for multi-layered learning system
    • Takahashi Y, Asada M. State-action space construction for multi-layered learning system. J Robot Soc Japan 2003;21:164-171.
    • (2003) J Robot Soc Japan , vol.21 , pp. 164-171
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    • Speeding up multiagent reinforcement learning by coarse-graining of perception: The hunter game
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    • Learning multiple goal behavior via task decomposition and dynamic policy merging
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    • Whitehead, S.1    Karlsson, J.2    Tenenberg, J.3
  • 14
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    • Reinforcement learning using a policy estimate of the other agent in a two-agent stochastic game
    • Nagayuki Y, Ito M. Reinforcement learning using a policy estimate of the other agent in a two-agent stochastic game. Trans IEICE 2003;J86-D-I:821-829.
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    • Nagayuki, Y.1    Ito, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.