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Volumn , Issue , 1998, Pages 1043-1049

Reinforcement learning with hierarchies of machines

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIOR-BASED; CONVERGENT ALGORITHMS; LEARNING PROCESS; NEW APPROACHES; PRIOR KNOWLEDGE; SEARCH SPACES;

EID: 84898956770     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (525)

References (19)
  • 1
    • 1142305413 scopus 로고
    • Reacting, planning and learning in an autonomous agent
    • K. Furukawa, D. Michie, and S. Muggleton, editors, Oxford University Press, Oxford
    • S. Benson and N. Nilsson. Reacting, planning and learning in an autonomous agent. In K. Furukawa, D. Michie, and S. Muggleton, editors, Machine Intelligence 14. Oxford University Press, Oxford, 1995.
    • (1995) Machine Intelligence , vol.14
    • Benson, S.1    Nilsson, N.2
  • 5
    • 0026255231 scopus 로고
    • O-plan: The open planning architecture
    • November
    • K. W. Currie and A. Tate. O-Plan: The Open Planning Architecture. Artificial Intelligence, 52(1), November 1991.
    • (1991) Artificial Intelligence , vol.52 , Issue.1
    • Currie, K.W.1    Tate, A.2
  • 6
    • 0001234682 scopus 로고
    • Feudal reinforcement learning
    • Stephen Jose Hanson, Jack D. Cowan, and C. Lee Giles, editors, San Mateo, California, Morgan Kaufman
    • P. Dayan and G. E. Hinton. Feudal reinforcement learning. In Stephen Jose Hanson, Jack D. Cowan, and C. Lee Giles, editors, Neural Information Processing Systems 5, San Mateo, California, 1993. Morgan Kaufman.
    • (1993) Neural Information Processing Systems , vol.5
    • Dayan, P.1    Hinton, G.E.2
  • 7
    • 0000746330 scopus 로고    scopus 로고
    • Model reduction techniques for computing approximately optimal solutions for markov decision processes
    • Providence, Rhode Island, August, Morgan Kaufmann
    • T. Dean, R. Givan, and S. Leach. Model reduction techniques for computing approximately optimal solutions for markov decision processes. In Proc. of the Thirteenth Conference on Un-certainty in Artificial Intelligence, Providence, Rhode Island, August 1997. Morgan Kaufmann.
    • (1997) Proc. of the Thirteenth Conference on Uncertainty in Artificial Intelligence
    • Dean, T.1    Givan, R.2    Leach, S.3
  • 9
    • 0344074989 scopus 로고    scopus 로고
    • Hierarchical reinforcement learning with the MAXQ value function decomposition
    • Oregon State University, Corvallis, Oregon
    • Thomas G. Dietterich. Hierarchical reinforcement learning with the MAXQ value function decomposition. Technical report, Department of Computer Science, Oregon State University, Corvallis, Oregon, 1997.
    • (1997) Technical Report, Department of Computer Science
    • Dietterich, T.G.1
  • 10
    • 84898980271 scopus 로고
    • Synthesizing efficient agents from partial programs
    • Proc. Charlotte, North Carolina, October, Springer-Verlag
    • Y.-J. Hsu. Synthesizing efficient agents from partial programs. In Methodologies for Intelligent Systems: 6th Int. Symposium, 1SM1S '91, Proc., Charlotte, North Carolina, October 1991. Springer-Verlag.
    • (1991) Methodologies for Intelligent Systems: 6th Int. Symposium, 1SM1S '91
    • Hsu, Y.-J.1
  • 11
    • 0000439891 scopus 로고
    • On the convergence of stochastic iterative dynamic programming algorithms
    • T. Jaakkola, M.I. Jordan, and S.P. Singh. On the convergence of stochastic iterative dynamic programming algorithms. Neural Computation, 6(6), 1994.
    • (1994) Neural Computation , vol.6 , Issue.6
    • Jaakkola, T.1    Jordan, M.I.2    Singh, S.P.3
  • 12
    • 0003673017 scopus 로고
    • PhD thesis, Computer Science Department, Carnegie-Mellon University, Pittsburgh, Pennsylvania
    • L.-J. Lin. Reinforcement Learning for Robots Using Neural Networks. PhD thesis, Computer Science Department, Carnegie-Mellon University, Pittsburgh, Pennsylvania, 1993.
    • (1993) Reinforcement Learning for Robots Using Neural Networks
    • Lin, L.-J.1
  • 13
    • 0347369287 scopus 로고    scopus 로고
    • PhD thesis, Computer Science Department, Brown University, Providence, Rhode Island
    • Shieu-Hong Lin. Exploiting Structure for Planning and Control. PhD thesis, Computer Science Department, Brown University, Providence, Rhode Island, 1997.
    • (1997) Exploiting Structure for Planning and Control
    • Lin, S.-H.1
  • 16
    • 0002876837 scopus 로고
    • Scaling reinforcement learning algorithms by learning variable temporal resolution models
    • Aberdeen, July, Morgan Kaufmann
    • S. P. Singh. Scaling reinforcement learning algorithms by learning variable temporal resolution models. In Proceedings of the Ninth International Conference on Machine Learning, Aberdeen, July 1992. Morgan Kaufmann.
    • (1992) Proceedings of the Ninth International Conference on Machine Learning
    • Singh, S.P.1
  • 17
    • 0001027894 scopus 로고
    • Transfer of learning by composing solutions of elemental sequential tasks
    • May
    • S. P. Singh. Transfer of learning by composing solutions of elemental sequential tasks. Machine Learning, 8(3), May 1992.
    • (1992) Machine Learning , vol.8 , Issue.3
    • Singh, S.P.1
  • 18
    • 0000224681 scopus 로고
    • Reinforcement learning with soft state aggregation
    • G. Tesauro, D. S. Touretzky, and T. K. Leen, editors, Cambridge, Massachusetts, MIT Press
    • S. P. Singh, T. Jaakola, and M. I. Jordan. Reinforcement learning with soft state aggregation. In G. Tesauro, D. S. Touretzky, and T. K. Leen, editors, Neural Information Processing Systems 7, Cambridge, Massachusetts, 1995. MIT Press.
    • (1995) Neural Information Processing Systems , vol.7
    • Singh, S.P.1    Jaakola, T.2    Jordan, M.I.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.