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Volumn , Issue , 2004, Pages 2-7

Performance bounded reinforcement learning in strategic interactions

Author keywords

[No Author keywords available]

Indexed keywords

AGENT TECHNOLOGIES; MUTLIAGENT LEARNING (MAL); REINFORCEMENT LEARNING; SUPPLY CHAIN MANAGEMENT;

EID: 9444299000     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (29)

References (30)
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  • 6
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    • The dynamics of reinforcement learning in cooperative multiagent systems
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    • Claus, C., and Boutilier, C. 1998. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the 15th National Conference on Artificial Intelligence, 746-752. Menlo Park, CA: AAAI Press/MIT Press.
    • (1998) Proceedings of the 15th National Conference on Artificial Intelligence , pp. 746-752
    • Claus, C.1    Boutilier, C.2
  • 7
    • 1942421183 scopus 로고    scopus 로고
    • AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents
    • Conitzer, V., and Sandholm, T. 2003a. AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents. In Proceedings of the 20th International Conference on Machine Learning.
    • (2003) Proceedings of the 20th International Conference on Machine Learning
    • Conitzer, V.1    Sandholm, T.2
  • 9
    • 0002267135 scopus 로고    scopus 로고
    • Adaptive game playing using multiplicative weights
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    • Freund, Y.1    Schapire, R.E.2
  • 14
    • 0000929496 scopus 로고    scopus 로고
    • Multiagent reinforcement learning: Theoretical framework and an algorithm
    • San Francisco, CA: Morgan Kaufmann
    • Hu, J., and Wellman, M. P. 1998. Multiagent reinforcement learning: Theoretical framework and an algorithm. In Proc. of the 15th Int. Conf. on Machine Learning (ML'98), 242-250. San Francisco, CA: Morgan Kaufmann.
    • (1998) Proc. of the 15th Int. Conf. on Machine Learning (ML'98) , pp. 242-250
    • Hu, J.1    Wellman, M.P.2
  • 19
    • 85149834820 scopus 로고
    • Markov games as a framework for multi-agent reinforcement learning
    • San Mateo, CA: Morgan Kaufmann
    • Littman, M. L. 1994. Markov games as a framework for multi-agent reinforcement learning. In Proc. of the 11th Int. Conf. on Machine Learning, 157-163. San Mateo, CA: Morgan Kaufmann.
    • (1994) Proc. of the 11th Int. Conf. on Machine Learning , pp. 157-163
    • Littman, M.L.1
  • 21
    • 0001730497 scopus 로고
    • Non-cooperative games
    • Nash, J.F. 1951. Non-cooperative games. Annals of Mathematics 54:286-295.
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    • On multiagent Q-learning in a semi-competitive domain
    • Weiß, G., and Sen, S., eds. Springer-Verlag
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    • Learning to coordinate without sharing information
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.