메뉴 건너뛰기




Volumn 18, Issue 6, 2003, Pages 316-324

A policy representation using weighted multiple normal distribution real-time reinforcement learning feasible for varying optimal actions

Author keywords

Actor critic; Hierarchical representation; Reinforcement learning; Robotics

Indexed keywords

ACTOR-CRITICS; HIERARCHICAL POLICIES; HIERARCHICAL REPRESENTATION; REINFORCEMENT LEARNING;

EID: 18444390265     PISSN: 13460714     EISSN: 13468030     Source Type: Journal    
DOI: 10.1527/tjsai.18.316     Document Type: Article
Times cited : (3)

References (17)
  • 1
    • 18444390925 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 2
    • 18444400290 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 3
    • 18444388898 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 4
    • 18444376801 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 5
    • 18444379102 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 6
    • 18444386869 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 7
    • 18444414628 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 8
    • 0030147547 scopus 로고    scopus 로고
    • Reinforcement learning for an ART-based fuzzy adaptive learning control network
    • [Lin 96]
    • [Lin 96] C. J. Lin and C. T. Lin: Reinforcement Learning for An ART-Based Fuzzy Adaptive Learning Control Network, IEEE Transactions on Neural Networks, Vol.7, No. 3, pp.709-731 (1996).
    • (1996) IEEE Transactions on Neural Networks , vol.7 , Issue.3 , pp. 709-731
    • Lin, C.J.1    Lin, C.T.2
  • 10
    • 18444380308 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 11
    • 18444367723 scopus 로고    scopus 로고
    • Japanese only
    • Japanese only
  • 12
    • 0031231885 scopus 로고    scopus 로고
    • Experiments with reinforcement learning in problems with continuous state and action spaces
    • [Santamaria 98]
    • [Santamaria 98] J. C. Santamaria, R. S. Sutton and A. Ram: Experiments with Reinforcement Learning in Problems with Continuous State and Action Spaces, Adaptive Behavior 6 (2), pp.163-218 (1998).
    • (1998) Adaptive Behavior , vol.6 , Issue.2 , pp. 163-218
    • Santamaria, J.C.1    Sutton, R.S.2    Ram, A.3
  • 14
    • 84898939480 scopus 로고    scopus 로고
    • Policy gradient methods for reinforcement learning with function approximation
    • [Sutton 00]
    • [Sutton 00] R. S. Sutton, D. McAllester, S. Singh, and Y. Mansour: Policy Gradient Methods for Reinforcement Learning with Function Approximation, Advances in Neural Information Processing Systems 12 (NIPS 12), pp. 1057-1063 (2000).
    • (2000) Advances in Neural Information Processing Systems , vol.12 , Issue.NIPS 12 , pp. 1057-1063
    • Sutton, R.S.1    McAllester, D.2    Singh, S.3    Mansour, Y.4
  • 16
    • 34249833101 scopus 로고
    • Technical note: Q-learning
    • [Watkins 92]
    • [Watkins 92] C. J. C. H. Watkins and P. Dayan: Technical Note: Q-Learning, Machine Learning 8, pp.279-292 (1992).
    • (1992) Machine Learning , vol.8 , pp. 279-292
    • Watkins, C.J.C.H.1    Dayan, P.2
  • 17
    • 0000337576 scopus 로고
    • Simple statistical gradient following algorithms for connectionist reinforcement learning
    • [Williams 92]
    • [Williams 92] R. J. Williams: Simple Statistical Gradient Following Algorithms for Connectionist Reinforcement Learning, Machine Learning 8, pp. 229-256 (1992).
    • (1992) Machine Learning , vol.8 , pp. 229-256
    • Williams, R.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.