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Volumn 141, Issue , 2006, Pages 494-498

Learning by automatic option discovery from conditionally terminating sequences

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY; TREES (MATHEMATICS);

EID: 84874712739     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: None     Document Type: Article
Times cited : (4)

References (10)
  • 1
    • 0141988716 scopus 로고    scopus 로고
    • Recent advances in hierarchical reinforcement learning
    • Andrew G. Barto and Sridhar Mahadevan, 'Recent advances in hierarchical reinforcement learning', Discrete Event Dynamic Systems, 13(4), 341-379, (2003).
    • (2003) Discrete Event Dynamic Systems , vol.13 , Issue.4 , pp. 341-379
    • Barto, A.G.1    Mahadevan, S.2
  • 2
    • 0002278788 scopus 로고    scopus 로고
    • Hierarchical reinforcement learning with the MAXQ value function decomposition
    • Thomas G. Dietterich, 'Hierarchical reinforcement learning with the MAXQ value function decomposition', Journal of AI Research, 13, 227-303, (2000).
    • (2000) Journal of AI Research , vol.13 , pp. 227-303
    • Dietterich, T.G.1
  • 5
    • 0013465187 scopus 로고    scopus 로고
    • Automatic discovery of subgoals in reinforcement learning using diverse density
    • Amy McGovern and Andrew G. Barto, 'Automatic discovery of subgoals in reinforcement learning using diverse density', in Proc. of Int. Conf. on Machine Learning, pp. 361-368, (2001).
    • (2001) Proc. of Int. Conf. on Machine Learning , pp. 361-368
    • McGovern, A.1    Barto, A.G.2
  • 7
    • 31844447221 scopus 로고    scopus 로고
    • Identifying useful subgoals in reinforcement learning by local graph partitioning
    • Özgur̈ Şimşek, Alicia P. Wolfe, and Andrew G. Barto, 'Identifying useful subgoals in reinforcement learning by local graph partitioning', in Proc. of Int. Conf. on Machine Learning, (2005).
    • (2005) Proc. of Int. Conf. on Machine Learning
    • Şimşek, O.1    Wolfe, A.P.2    Barto, A.G.3
  • 10
    • 0033170372 scopus 로고    scopus 로고
    • Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
    • Richard S. Sutton, Doina Precup, and Satinder Singh, 'Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning', Artificial Intelligence, 112(1-2), 181-211, (1999).
    • (1999) Artificial Intelligence , vol.112 , Issue.1-2 , pp. 181-211
    • Sutton, R.S.1    Precup, D.2    Singh, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.