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Volumn , Issue , 2013, Pages 2540-2544

Model-based indirect learning method based on dyna-Q architecture

Author keywords

Decision tree; Dyna Q; Model learning

Indexed keywords

DYNA-Q; ENVIRONMENT MODELING; INDIRECT LEARNING; MODEL LEARNING; Q-LEARNING ALGORITHMS; STOCHASTIC ENVIRONMENT; TREE STRUCTURES; VALUE ITERATION;

EID: 84893626354     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SMC.2013.433     Document Type: Conference Paper
Times cited : (5)

References (7)
  • 3
    • 79953906172 scopus 로고    scopus 로고
    • Self-organizing state aggregation for architecture design of q-learning
    • K. S. Hwang, H. Y. Lin, Y. P. Hsu and H. H. Yu, "Self-organizing state aggregation for architecture design of Q-learning, " Information Sciences, vol.181, pp.2813-2822, 2011.
    • (2011) Information Sciences , vol.181 , pp. 2813-2822
    • Hwang, K.S.1    Lin, H.Y.2    Hsu, Y.P.3    Yu, H.H.4
  • 5
    • 85132026293 scopus 로고
    • Integrated architectures for learning, planning, and reacting based on approximating dynamic programming
    • R.S. Sutton, "Integrated architectures for learning, planning, and reacting based on approximating dynamic programming, " Proceedings of the Seventh International Conference on Machine Learning, pp. 216- 224, 1990.
    • (1990) Proceedings of the Seventh International Conference on Machine Learning , pp. 216-224
    • Sutton, R.S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.