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Volumn 43, Issue 5, 2006, Pages 851-855

K-cluster Subgoal discovery algorithm for Option

Author keywords

Hierarchical reinforcement learning; Option; Subgoal

Indexed keywords

HIERARCHICAL SYSTEMS; PERFORMANCE; REINFORCEMENT; SOFTWARE AGENTS; TRAJECTORIES;

EID: 33745937922     PISSN: 10001239     EISSN: None     Source Type: Journal    
DOI: 10.1360/crad20060512     Document Type: Article
Times cited : (4)

References (8)
  • 1
    • 0033170372 scopus 로고    scopus 로고
    • Between MDPs and semiMDPs: A framework for temporal abstraction in reinforcement learning
    • R. S. Sutton, D. Precup, S. Singh. Between MDPs and semiMDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence, 1999, 112(1/2): 181-211
    • (1999) Artificial Intelligence , vol.112 , Issue.1-2 , pp. 181-211
    • Sutton, R.S.1    Precup, D.2    Singh, S.3
  • 3
    • 0002278788 scopus 로고    scopus 로고
    • Hierarchical reinforcement learning with the MAXQ value function decomposition
    • T. G. Dietterich. Hierarchical reinforcement learning with the MAXQ value function decomposition. Journal of Artificial Intelligence Research, 2000, 13: 227-303
    • (2000) Journal of Artificial Intelligence Research , vol.13 , pp. 227-303
    • Dietterich, T.G.1
  • 4
    • 33745958930 scopus 로고    scopus 로고
    • Improved automatic discovery of subgoals for options in hierarchical reinforcement learning
    • R. Matthew Kretchmar, Todd Feil, Rohit Bansal. Improved automatic discovery of subgoals for options in hierarchical reinforcement learning. Journal of Computer Science and Technology, 2003, 3(2): 9-14
    • (2003) Journal of Computer Science and Technology , vol.3 , Issue.2 , pp. 9-14
    • Kretchmar, R.M.1    Feil, T.2    Bansal, R.3
  • 6
    • 0013465187 scopus 로고    scopus 로고
    • Automatic discovery of subgoals in reinforcement learning using diverse density
    • San Francisco, CA: Morgan Kaufmann
    • A. McGovern, A. Barto. Automatic discovery of subgoals in reinforcement learning using diverse density. In: Proc. 18th Int'l Conf. Machine Learning. San Francisco, CA: Morgan Kaufmann, 2001. 361-368
    • (2001) Proc. 18th Int'l Conf. Machine Learning , pp. 361-368
    • McGovern, A.1    Barto, A.2
  • 8
    • 0000123778 scopus 로고
    • Self-improving agents based on reinforcement learning, planning and teaching
    • L. Lin. Self-improving agents based on reinforcement learning, planning and teaching. Machine Learning, 1992, 8(3): 293-321
    • (1992) Machine Learning , vol.8 , Issue.3 , pp. 293-321
    • Lin, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.