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Volumn 4, Issue , 2003, Pages 3062-3067

An adjustment method of the number of states on Q-learning segmenting state space adaptively

Author keywords

Adaptive learning; Autonomous behavior; Q learning; QLASS; Reinforcement learning

Indexed keywords

AUTONOMOUS AGENTS; LEARNING ALGORITHMS; MOBILE ROBOTS; PROBABILITY DISTRIBUTIONS; RANDOM PROCESSES; STATE SPACE METHODS;

EID: 0242721808     PISSN: 08843627     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (11)
  • 1
    • 72949120761 scopus 로고    scopus 로고
    • Efficient, globally-optimized reinforcement learning with the parti-game algorithm
    • The MIT Press
    • M. A. Al-Ansari and R. J. Williams, "Efficient, globally-optimized reinforcement learning with the parti-game algorithm," Advances in Neural Information Processing Systems, 11, The MIT Press, 1999.
    • (1999) Advances in Neural Information Processing Systems , vol.11
    • Al-Ansari, M.A.1    Williams, R.J.2
  • 3
    • 0016557674 scopus 로고
    • Multidimensional binary search trees used for associative searching
    • J. L. Bentley, "Multidimensional binary search trees used for associative searching," Communications of the ACM, vol.18, No.9, pp.509-517, 1975.
    • (1975) Communications of the ACM , vol.18 , Issue.9 , pp. 509-517
    • Bentley, J.L.1
  • 5
    • 0029514510 scopus 로고
    • The parti-game algorithm for variable resolution reinforcement learning in multidimensional state-spaces
    • A. W. Moore and C. G. Atkeson, "The parti-game algorithm for variable resolution reinforcement learning in multidimensional state-spaces," Machine Learning, 21, pp.199-233, 1995.
    • (1995) Machine Learning , vol.21 , pp. 199-233
    • Moore, A.W.1    Atkeson, C.G.2
  • 8
    • 0242536865 scopus 로고    scopus 로고
    • Adaptive resolution model-free reinforcement learning: Decision boundary partitioning
    • S. I. Reynolds, "Adaptive resolution model-free reinforcement learning: decision boundary partitioning," Proc. 17th International Conf. on Machine Learning, pp.783-790, 2000.
    • (2000) Proc. 17th International Conf. on Machine Learning , pp. 783-790
    • Reynolds, S.I.1
  • 9
    • 0033213823 scopus 로고    scopus 로고
    • Adaptive internal state space construction method for reinforcement learning of a real-world agent
    • K. Samejima and T. Omori, "Adaptive internal state space construction method for reinforcement learning of a real-world agent," Neural Networks, vol.11, pp.1143-1155, 1999.
    • (1999) Neural Networks , vol.11 , pp. 1143-1155
    • Samejima, K.1    Omori, T.2
  • 11


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.