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Volumn , Issue , 2005, Pages 69-74

Reinforcement learning acceleration through autonomous subgoal discovery

Author keywords

[No Author keywords available]

Indexed keywords

ACTION SPACES; HIERARCHICAL STATE; LEARNING TIME; REINFORCEMENT LEARNING AGENTS; STATE SPACES; SUBGOALS; TIME SPENT;

EID: 60749083025     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (10)
  • 1
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    • Hierarchical control and learning for markov decision processes,
    • Ph.D. dissertation, University of California, Berkeley, CA
    • R. Parr, "Hierarchical control and learning for markov decision processes," Ph.D. dissertation, University of California, Berkeley, CA, 1998.
    • (1998)
    • Parr, R.1
  • 2
    • 84942867726 scopus 로고    scopus 로고
    • An overview of maxq hierarchical reinforcement learning
    • T. G. Dietterich, "An overview of maxq hierarchical reinforcement learning," Lecture Notes in Computer Science, vol. 1864, 2000.
    • (2000) Lecture Notes in Computer Science , vol.1864
    • Dietterich, T.G.1
  • 3
    • 0007907759 scopus 로고    scopus 로고
    • Emergent hierarchical control structures: Learning reactive / hierarchical relationships in reinforcement environments
    • B. Digney, "Emergent hierarchical control structures: Learning reactive / hierarchical relationships in reinforcement environments," in Proceedings of the Fourth Conference on the Simulation of Adaptive Behavior, 1996.
    • (1996) Proceedings of the Fourth Conference on the Simulation of Adaptive Behavior
    • Digney, B.1
  • 6
    • 0034272032 scopus 로고    scopus 로고
    • Bounded-parameter markov decision processes
    • R. Givan, S. Leach, and T. Dean, "Bounded-parameter markov decision processes," Artificial Intelligence, vol. 122, no. 1-2, pp. 71-109, 2000.
    • (2000) Artificial Intelligence , vol.122 , Issue.1-2 , pp. 71-109
    • Givan, R.1    Leach, S.2    Dean, T.3
  • 7
    • 0346942368 scopus 로고    scopus 로고
    • Decision-theoretic planning: Structural assumptions and computational leverage
    • C. Boutilier, T. Dean, and S. Hanks, "Decision-theoretic planning: Structural assumptions and computational leverage," Journal of Artificial Intelligence Research, vol. 11, pp. 1-94, 1999.
    • (1999) Journal of Artificial Intelligence Research , vol.11 , pp. 1-94
    • Boutilier, C.1    Dean, T.2    Hanks, S.3
  • 8
    • 0033170372 scopus 로고    scopus 로고
    • Between MDPs and Semi-MDPs: Learning, planning, and representing knowledge at multiple temporal scales
    • R. Sutton, D. Precup, and S. Singh, "Between MDPs and Semi-MDPs: Learning, planning, and representing knowledge at multiple temporal scales," Artificial Intelligence, vol. 112, pp. 181-211, 1999.
    • (1999) Artificial Intelligence , vol.112 , pp. 181-211
    • Sutton, R.1    Precup, D.2    Singh, S.3
  • 9
    • 0038178323 scopus 로고    scopus 로고
    • Solving factored MDPs using non-homogeneous partitions
    • K. Kim and T. Dean, "Solving factored MDPs using non-homogeneous partitions," Artificial Intelligence, vol. 147, pp. 225-251, 2003.
    • (2003) Artificial Intelligence , vol.147 , pp. 225-251
    • Kim, K.1    Dean, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.