메뉴 건너뛰기




Volumn , Issue , 2005, Pages 779-785

Concurrent hierarchical reinforcement learning

Author keywords

[No Author keywords available]

Indexed keywords

DECISION POINTS; HIERARCHICAL REINFORCEMENT LEARNING; MULTITHREADED; PRIOR KNOWLEDGE;

EID: 84880718755     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (63)

References (12)
  • 1
    • 0012312949 scopus 로고    scopus 로고
    • State abstraction for programmable reinforcement learning agents
    • D. Andre and S. Russell. State abstraction for programmable reinforcement learning agents. In AAAI, 2002.
    • (2002) AAAI
    • Andre, D.1    Russell, S.2
  • 3
    • 0033188982 scopus 로고    scopus 로고
    • Bucket elimination: A unifying framework for reasoning
    • DOI 10.1016/S0004-3702(99)00059-4
    • R. Dechter. Bucket elimination : a unifying framework for reasoning. Artificial Intelligence, 113:41-85, 1999. (Pubitemid 30542742)
    • (1999) Artificial Intelligence , vol.113 , Issue.1 , pp. 41-85
    • Dechter, R.1
  • 4
    • 0002278788 scopus 로고    scopus 로고
    • Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
    • T. Dietterich. Hierarchical reinforcement learning with the maxq value function decomposition. JAIR, 13:227-303, 2000. (Pubitemid 33682087)
    • (2000) Journal of Artificial Intelligence Research , vol.13 , pp. 227-303
    • Dietterich, T.G.1
  • 6
    • 84880803349 scopus 로고    scopus 로고
    • Generalizing plans to new environments in relational MDPs
    • C. Guestrin, D. Koller, C. Gearhart, and N. Kanodia. Generalizing plans to new environments in relational MDPs. In IJCAI, 2003.
    • (2003) IJCAI
    • Guestrin, C.1    Koller, D.2    Gearhart, C.3    Kanodia, N.4
  • 7
    • 0034819292 scopus 로고    scopus 로고
    • Hierarchical multi-agent reinforcement learning
    • R. Makar, S. Mahadevan, and M. Ghavamzadeh. Hierarchical multi-agent reinforcement learning. In ICRA, 2001.
    • (2001) ICRA
    • Makar, R.1    Mahadevan, S.2    Ghavamzadeh, M.3
  • 8
    • 0141596576 scopus 로고    scopus 로고
    • Policy invariance under reward transformations: Theory and application to reward shaping
    • A. Ng, D. Harada, and S. Russell. Policy invariance under reward transformations : theory and application to reward shaping. In ICML, 1999.
    • (1999) ICML
    • Ng, A.1    Harada, D.2    Russell, S.3
  • 11
    • 84899024675 scopus 로고    scopus 로고
    • Learning to take concurrent actions
    • K. Rohanimanesh and S. Mahadevan. Learning to take concurrent actions. In NIPS. 2003.
    • (2003) NIPS
    • Rohanimanesh, K.1    Mahadevan, S.2
  • 12
    • 1942484759 scopus 로고    scopus 로고
    • Q-decomposition for reinforcement learning agents
    • S. Russell and A. Zimdars. Q-decomposition for reinforcement learning agents. In ICML, 2003.
    • (2003) ICML
    • Russell, S.1    Zimdars, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.