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Volumn , Issue , 2007, Pages 819-824

NEFRL: A new neuro-fuzzy system for episodic reinforcement learning tasks

Author keywords

[No Author keywords available]

Indexed keywords

DOMAIN KNOWLEDGE; INPUT-OUTPUT; LOCAL MAXIMUM; NEURO-FUZZY ARCHITECTURES; NEURO-FUZZY SYSTEMS; NUMERICAL EVALUATIONS; NUMERICAL PERFORMANCE;

EID: 49349103392     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FBIT.2007.139     Document Type: Conference Paper
Times cited : (2)

References (12)
  • 3
    • 0031631272 scopus 로고    scopus 로고
    • A Neuro-Fuzzy Approach to Obtain Interpretable Fuzzy Systems for Function Approximation
    • D. Nauck and R. Kruse, "A Neuro-Fuzzy Approach to Obtain Interpretable Fuzzy Systems for Function Approximation," in IEEE International Conference on Fuzzy Systems, 1998.
    • (1998) IEEE International Conference on Fuzzy Systems
    • Nauck, D.1    Kruse, R.2
  • 9
    • 49349116670 scopus 로고    scopus 로고
    • Can Cerebella Cortex Learn Any Non-linear Function
    • preprint
    • M.M. Ebadzadeh, R.Gentili, and C. Darlot, "Can Cerebella Cortex Learn Any Non-linear Function," preprint.
    • Ebadzadeh, M.M.1    Gentili, R.2    Darlot, C.3
  • 10
    • 0035249254 scopus 로고    scopus 로고
    • Simulation-Based Optimization of Markov Reward Processes
    • P. Marbach and J.N. Tsitsiklis, "Simulation-Based Optimization of Markov Reward Processes," IEEE Transaction on Automatic Control, vol. 46, no. 2, pp. 191-209, 2001.
    • (2001) IEEE Transaction on Automatic Control , vol.46 , Issue.2 , pp. 191-209
    • Marbach, P.1    Tsitsiklis, J.N.2
  • 12


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.