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Volumn , Issue , 2008, Pages 1208-1215

Preconditioned temporal difference learning

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; ITERATIVE METHODS; MACHINE LEARNING; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; EDUCATION; LEARNING SYSTEMS; ROBOT LEARNING;

EID: 56449123618     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1390156.1390308     Document Type: Conference Paper
Times cited : (20)

References (13)
  • 2
    • 0001771345 scopus 로고    scopus 로고
    • Linear least-squares algorithms for temporal difference learning
    • Bradtke, S., & Barto, A. G. (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.G.2
  • 5
    • 0012331016 scopus 로고
    • Memory approaches to reinforcement learning in non-markovian domains
    • CMU-CS-92-138, Carnegie Mellon University, Pittsburgh, PA 15213
    • Lin, L.-J., & Mitchell, T. M. (1992). Memory approaches to reinforcement learning in non-markovian domains (Technical Report CMU-CS-92-138). Carnegie Mellon University, Pittsburgh, PA 15213.
    • (1992) Technical Report
    • Lin, L.-J.1    Mitchell, T.M.2
  • 6
    • 0037288398 scopus 로고    scopus 로고
    • Least-squares policy evaluation algorithms with linear function approximation
    • Nedić, A., & Bertsekas, D. P. (2003). Least-squares policy evaluation algorithms with linear function approximation. Journal of Discrete Event Systems, 13, 79-110.
    • (2003) Journal of Discrete Event Systems , vol.13 , pp. 79-110
    • Nedić, A.1    Bertsekas, D.P.2
  • 8
    • 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
  • 10
    • 0035283402 scopus 로고    scopus 로고
    • On the convergence of temporal-difference learning with linear function approximation
    • Tadić, V. (2001). On the convergence of temporal-difference learning with linear function approximation. Machine Learning, 42, 241-267.
    • (2001) Machine Learning , vol.42 , pp. 241-267
    • Tadić, V.1
  • 11
    • 0031143730 scopus 로고    scopus 로고
    • An analysis of temporal-difference learning with function approximation
    • Tsitsiklis, J. N., & Van Roy, B. (1997). An analysis of temporal-difference learning with function approximation. IEEE Transactions on Automatic Control, 42, 674-690.
    • (1997) IEEE Transactions on Automatic Control , vol.42 , pp. 674-690
    • Tsitsiklis, J.N.1    Van Roy, B.2
  • 12
    • 0041345290 scopus 로고    scopus 로고
    • Efficient reinforcement learning using recursive least-squares methods
    • Xu, X., He, H., & 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
  • 13
    • 56449128935 scopus 로고    scopus 로고
    • Preconditioned temporal difference learning
    • CityU-SCM-MCG-0408, City University of Hong Kong
    • Yao, H., & Liu, Z. (2008). Preconditioned temporal difference learning (Technical Report CityU-SCM-MCG-0408). City University of Hong Kong.
    • (2008) Technical Report
    • Yao, H.1    Liu, Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.