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Volumn 2714, Issue , 2003, Pages 479-487

Learning to control at multiple time scales

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPLEX NETWORKS; ECONOMIC AND SOCIAL EFFECTS; NEURAL NETWORKS; REINFORCEMENT LEARNING; TIME MEASUREMENT;

EID: 35248821170     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44989-2_57     Document Type: Article
Times cited : (10)

References (8)
  • 1
    • 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, 13:227-303, 2000.
    • (2000) Journal of Artificial Intelligence Research , vol.13 , pp. 227-303
    • Dietterich, T.G.1
  • 2
    • 0039225087 scopus 로고    scopus 로고
    • Adaptive choice of grid and time in reinforcement learning
    • MIT Press
    • S. Pareigis. Adaptive choice of grid and time in reinforcement learning. NIPS, volume 10. MIT Press, 1998.
    • (1998) NIPS , vol.10
    • Pareigis, S.1
  • 4
    • 0345062532 scopus 로고    scopus 로고
    • High quality thermostat control by reinforcement learning - A case study
    • CMU
    • M. Riedmiller. High quality thermostat control by reinforcement learning - a case study. In Proceedings of the Conald Workshop 1998, CMU, 1998.
    • (1998) Proceedings of the Conald Workshop 1998
    • Riedmiller, M.1
  • 5
    • 0033233953 scopus 로고    scopus 로고
    • Concepts and facilities of a neural reinforcement learning control architecture for technical process control
    • M. Riedmiller. Concepts and facilities of a neural reinforcement learning control architecture for technical process control. Journal of Neural Computing and Application, 8:323-338, 2000.
    • (2000) Journal of Neural Computing and Application , vol.8 , pp. 323-338
    • Riedmiller, M.1
  • 6
    • 35248820427 scopus 로고    scopus 로고
    • Speeding-up reinforcement learning with multi-step actions
    • ICANN, Springer
    • R. Schoknecht and M. Riedmiller. Speeding-up reinforcement learning with multi-step actions. ICANN, LNCS 2415, pages 813-818, 2002. Springer.
    • (2002) LNCS , vol.2415 , pp. 813-818
    • Schoknecht, R.1    Riedmiller, M.2
  • 7
    • 85156221438 scopus 로고    scopus 로고
    • Generalization in reinforcement learning: Successful examples using sparse coarse coding
    • MIT Press
    • R. S. Sutton. Generalization in reinforcement learning: Successful examples using sparse coarse coding. NIPS, volume 8, pages 1038-1044. MIT Press, 1996.
    • (1996) NIPS , vol.8 , pp. 1038-1044
    • Sutton, R.S.1
  • 8
    • 0033170372 scopus 로고    scopus 로고
    • Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning
    • R. S. Sutton, D. Precup, and S. Singh. Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning. AI, 112:181-211, 1999.
    • (1999) AI , vol.112 , pp. 181-211
    • Sutton, R.S.1    Precup, D.2    Singh, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.