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Volumn , Issue , 2007, Pages 1136-1143

On discovery and learning of models with predictive representations of state for agents with continuous actions and observations

Author keywords

Dynamical system modeling; Information theory; Predictive representations of state

Indexed keywords

CONTINUOUS OBSERVATIONS; KERNEL DENSITY ESTIMATIONS; MATRIXES; MODEL PARAMETERS; MODELING METHODS; PREDICTIVE REPRESENTATIONS OF STATE; PREDICTIVE STATE REPRESENTATIONS; SUFFICIENT STATISTICS; SYSTEM DYNAMICS;

EID: 60349110114     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1329125.1329352     Document Type: Conference Paper
Times cited : (12)

References (18)
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    • Y. Engel, S. Mannor, and R. Meir. Bayes meets bellman: The gaussian process approach to temporal difference learning. In ICML, 2003.
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  • 4
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    • Learning and discovery of predictive state representations in dynamical systems with reset
    • M. R. James and S. Singh. Learning and discovery of predictive state representations in dynamical systems with reset. In ICML, pages 417-424, 2004.
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    • James, M.R.1    Singh, S.2
  • 6
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    • Predictive representations of state
    • M. L. Littman, R. S. Sutton, and S. Singh. Predictive representations of state. In NIPS, pages 1555-1561, 2002.
    • (2002) NIPS , pp. 1555-1561
    • Littman, M.L.1    Sutton, R.S.2    Singh, S.3
  • 7
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    • Online discovery and learning of predictive state representations
    • P. McCracken and M. Bowling. Online discovery and learning of predictive state representations. In NIPS, pages 875-882, 2006.
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    • McCracken, P.1    Bowling, M.2
  • 9
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    • Using predictive representations to improve generalization in reinforcement learning
    • E. J. Rafols, M. B. Ring, R. S. Sutton, and B. Tanner. Using predictive representations to improve generalization in reinforcement learning. In IJCAI, pages 835-840, 2005.
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  • 10
    • 33749256805 scopus 로고    scopus 로고
    • Predictive linear-Gaussian models of controlled stochastic dynamical systems
    • M. Rudary and S. Singh. Predictive linear-Gaussian models of controlled stochastic dynamical systems. In ICML, 2006.
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  • 11
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    • Predictive linear-Gaussian models of stochastic dynamical systems
    • M. Rudary, S. Singh, and D. Wingate. Predictive linear-Gaussian models of stochastic dynamical systems. In UAI, pages 501-508, 2005.
    • (2005) UAI , pp. 501-508
    • Rudary, M.1    Singh, S.2    Wingate, D.3
  • 12
    • 33749263456 scopus 로고    scopus 로고
    • Predictive state representations: A new theory for modeling dynamical systems
    • S. Singh, M. R. James, and M. R. Rudary. Predictive state representations: A new theory for modeling dynamical systems. In UAI, pages 512-519, 2004.
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  • 13
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    • K. Tbrkkola. Feature extraction by non-parametric mutual information maximization. Journal of Machine Learning Research, (3):1415-1438, 2003.
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  • 14
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  • 15
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    • Kernel predictive linear Gaussian models for nonlinear stochastic dynamical systems
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  • 17
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    • D. Wingate, V. Soni, B. Wolfe, and S. Singh. Relational knowledge with predictive representations of state. In IJCAI, 2007.
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  • 18
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.