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Volumn 1, Issue , 2006, Pages 356-361

Incremental least-squares temporal difference learning

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; LEAST SQUARES APPROXIMATIONS; PUBLIC POLICY;

EID: 33750737011     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (52)

References (15)
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    • A theory of cerebellar function
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    • Albus, J.S.1
  • 3
    • 0036832950 scopus 로고    scopus 로고
    • Technical update: Least-squares temporal difference learning
    • Boyan, J. A. 2002. Technical update: Least-squares temporal difference learning. Machine Learning 49:233-246.
    • (2002) Machine Learning , vol.49 , pp. 233-246
    • Boyan, J.A.1
  • 4
    • 0001771345 scopus 로고    scopus 로고
    • Linear least-squares algorithms for temporal difference learning
    • Bradtke, S., and Barto, A. 1996. Linear least-squares algorithms for temporal difference learning. Machine Learning 22:33-57.
    • (1996) Machine Learning , vol.22 , pp. 33-57
    • Bradtke, S.1    Barto, A.2
  • 7
    • 0027684215 scopus 로고
    • Prioritized sweeping: Reinforcement learning with less data and less time
    • Moore, A. W., and Atkeson, C. G. 1993. Prioritized sweeping: Reinforcement learning with less data and less time. Machine Learning 13:103-130.
    • (1993) Machine Learning , vol.13 , pp. 103-130
    • Moore, A.W.1    Atkeson, C.G.2
  • 11
    • 33847202724 scopus 로고
    • Learning to predict by the methods of temporal differences
    • Sutton, R. S. 1988. Learning to predict by the methods of temporal differences. Machine Learning 3:9-44.
    • (1988) Machine Learning , vol.3 , pp. 9-44
    • Sutton, R.S.1
  • 12
    • 85156221438 scopus 로고    scopus 로고
    • Generalization in reinforcement learning: Successful examples using sparse coarse coding
    • Touretzky, D. S.; Mozer, M. C.; and Hasselmo, M. E., eds., The MIT Press
    • Sutton, R. S. 1996. Generalization in reinforcement learning: Successful examples using sparse coarse coding. In Touretzky, D. S.; Mozer, M. C.; and Hasselmo, M. E., eds., Advances in Neural Information Processing Systems 8, 1038-1044. The MIT Press.
    • (1996) Advances in Neural Information Processing Systems , vol.8 , pp. 1038-1044
    • Sutton, R.S.1
  • 14
    • 0031143730 scopus 로고    scopus 로고
    • An analysis of temporal-difference learning with function approximation
    • Tsitsiklis, J. N., and Van Roy, B. 1997. An analysis of temporal-difference learning with function approximation. IEEE Transactions on Automatic Control 42(5):674-690.
    • (1997) IEEE Transactions on Automatic Control , vol.42 , Issue.5 , pp. 674-690
    • Tsitsiklis, J.N.1    Van Roy, B.2
  • 15
    • 0041345290 scopus 로고    scopus 로고
    • Efficient reinforcement learning using recursive least-squares methods
    • Xu, X.; He, H.; and Hu, D. 2002. Efficient reinforcement learning using recursive least-squares methods. Journal of Artificial Intelligence Research 16:259-292.
    • (2002) Journal of Artificial Intelligence Research , vol.16 , pp. 259-292
    • Xu, X.1    He, H.2    Hu, D.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.