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Volumn 2457, Issue , 2002, Pages 264-272

Minimax fuzzy Q-learning in cooperative multi-agent systems

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION SYSTEMS; INFORMATION USE; MACHINE LEARNING; OPTIMIZATION; REINFORCEMENT LEARNING;

EID: 80053654030     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-36077-8_27     Document Type: Conference Paper
Times cited : (3)

References (28)
  • 1
    • 84951728431 scopus 로고
    • PhD Thesis, University of Cambridge, England
    • Waduns, C. J. C. H., "Learnzng pom delayed rewards", PhD Thesis, University of Cambridge, England, 1989.
    • (1989) Learnzng Pom Delayed Rewards
    • Waduns, C.1
  • 10
    • 0030050933 scopus 로고
    • Multi agent reinforcement learning in the Iterated Prisoners Dilemma”
    • Sandholm, T.W.; Crites, R. H., “Multi agent reinforcement learning in the Iterated Prisoner’s Dilemma”, Biosystems, 37:147–166, 1995.
    • (1995) Biosystems , vol.37 , pp. 147-166
    • Sandholm, T.W.1    Crites, R.H.2
  • 13
    • 0000123778 scopus 로고
    • Self-improving reactive agents based on reinforcement learning, planning and teaching
    • Lin, L. J. ,“Self-improving reactive agents based on reinforcement learning, planning and teaching“, Machine Learning, Vol: 8, pp: 293-321, 1992.
    • (1992) Machine Learning , vol.8 , pp. 293-332
    • Lin, L.J.1
  • 18
    • 34249833101 scopus 로고
    • Technical Note: Q-Learning
    • Watkins, C. J. C. H.; Dayan P., “Technical Note: Q-Learning” Machine Learning, 8:279-292, 1992.
    • (1992) Machine Learning , vol.8 , pp. 279-292
    • Watkins, C.1    Dayan, P.2
  • 19
    • 0001547175 scopus 로고    scopus 로고
    • Value-function reinforcement learning in Markov games
    • Littman, M. L., “Value-function reinforcement learning in Markov games”, Journal of Cognitive Systems Research, vol: 2, pp: 55–66, 2001.
    • (2001) Journal of Cognitive Systems Research , vol.2 , pp. 55-66
    • Littman, M.L.1
  • 21
    • 0026923465 scopus 로고
    • Learning and tuning fuzzy logic controllers through reinforcement
    • Sept
    • Berenji, H.; Khedkar, P., “Learning and tuning fuzzy logic controllers through reinforcement”, IEEE Trans. on Neural Networks, 3(5), Sept. 1992.
    • (1992) IEEE Trans. On Neural Networks , vol.3 , Issue.5
    • Berenji, H.1    Khedkar, P.2
  • 22
    • 84951808510 scopus 로고    scopus 로고
    • Reinforcement learning for autonomous robots
    • Aachen, Germany, Sept
    • Glorennec, P. Y.; Jouffe, L., “Reinforcement learning for autonomous robots”, Proc. of EUFIT, Aachen, Germany, Sept., 1996.
    • (1996) Proc. Of EUFIT
    • Glorennec, P.Y.1    Jouffe, L.2
  • 23
    • 0029287724 scopus 로고
    • Fuzzy logic controllers are universal approximators
    • April
    • Castro, J. L., “Fuzzy logic controllers are universal approximators”, IEEE Transaction on SMC, vol: 25/4, April, 1995.
    • (1995) IEEE Transaction on SMC , vol.25 , Issue.4
    • Castro, J.L.1
  • 24
    • 11744283659 scopus 로고
    • Fuzzy Q-learning and evolutionary Strategy for adaptive fuzzy control
    • Aachen, Germany, Sept
    • Glorennec, P. Y., “Fuzzy Q-learning and evolutionary Strategy for adaptive fuzzy control”, Proc. of EUFIT, ELITE Foundation, pp: 35-40, Aachen, Germany, Sept., 1994.
    • (1994) Proc. Of EUFIT, ELITE Foundation , pp. 35-40
    • Glorennec, P.Y.1
  • 25
    • 0028731609 scopus 로고
    • Fuzzy Q-learning: A new approach for fuzzy dynamic programming
    • IEEE Computer Press, Piscataway, NJ
    • Berenji, H. R., “Fuzzy Q-learning: a new approach for fuzzy dynamic programming”, Proc. Third IEEE Int. Conf. on Fuzzy Systems. IEEE Computer Press, Piscataway, NJ, pp: 486–491, 1994.
    • (1994) Proc. Third IEEE Int. Conf. On Fuzzy Systems , pp. 486-549
    • Berenji, H.R.1
  • 26
    • 0003330984 scopus 로고    scopus 로고
    • Delayed reinforcement, Fuzzy Q-learning and Fuzzy Logic Controllers
    • Physica Verlag (Springer Verlag), Heidelberg, Germany
    • Bonarini, A., “Delayed reinforcement, Fuzzy Q-learning and Fuzzy Logic Controllers”, Genetic Algorithms and Soft Computing, Physica Verlag (Springer Verlag), Heidelberg, Germany, pp: 447–466, 1996b.
    • (1996) Genetic Algorithms and Soft Computing , pp. 447-466
    • Bonarini, A.1
  • 27
    • 0001435241 scopus 로고    scopus 로고
    • Multi-agent Reinforcement Learning: An Approach Based On The Other Agent’s Internal Model
    • 215–221, Los Alamitos, IEEE Computer Society
    • Nagayuki, Y.; Ishii, S.; Kenji, D., “Multi-agent Reinforcement Learning: An Approach Based On The Other Agent’s Internal Model”, Fourth International Conference on Multiagent Systems (ICMAS), 215–221, Los Alamitos, IEEE Computer Society, 2000.
    • (2000) Fourth International Conference on Multiagent Systems (ICMAS)
    • Nagayuki, Y.1    Ishii, S.2    Kenji, D.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.