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Volumn 2006, Issue , 2006, Pages 850-857

Learning the task allocation game

Author keywords

Markov decision process; Multiagent systems; Reinforcement learning; Task allocation

Indexed keywords

MARKOV DECISION PROCESSES; OPTIMAL GLOBAL SOLUTIONS; SHAPLEY'S GAMES; TASK ALLOCATION;

EID: 34247227200     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1160633.1160786     Document Type: Conference Paper
Times cited : (56)

References (10)
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    • Bowling, M.1
  • 3
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    • Bowling, M.1    Veloso, M.2
  • 4
    • 0031630561 scopus 로고    scopus 로고
    • The dynamics of reinforcement learning in cooperative multiagent systems
    • C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In AAAI/IAAI, pages 746-752, 1998.
    • (1998) AAAI/IAAI , pp. 746-752
    • Claus, C.1    Boutilier, C.2
  • 5
    • 1942421183 scopus 로고    scopus 로고
    • Awesome: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents
    • V. Conitzer and T. Sandholm. Awesome: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents. In International Conference on Machine Learning, pages 83-90, 2003.
    • (2003) International Conference on Machine Learning , pp. 83-90
    • Conitzer, V.1    Sandholm, T.2
  • 6
    • 4644369748 scopus 로고    scopus 로고
    • Nash q-learning for general-sum stochastic games
    • J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039-1069, 2003.
    • (2003) Journal of Machine Learning Research , vol.4 , pp. 1039-1069
    • Hu, J.1    Wellman, M.P.2
  • 9
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    • Reinforcement learning to play an optimal nash equilibrium in team markov games
    • S. T. S. Becker and K. Obermayer, editors, MIT Press
    • X. Wang and T. Sandholm. Reinforcement learning to play an optimal nash equilibrium in team markov games. In S. T. S. Becker and K. Obermayer, editors, Advances in Neural Information Processing Systems 15. MIT Press.
    • Advances in Neural Information Processing Systems 15
    • Wang, X.1    Sandholm, T.2
  • 10
    • 1942484421 scopus 로고    scopus 로고
    • Online convex programming and generalized infinitesimal gradient ascent
    • M. Zinkevich. Online convex programming and generalized infinitesimal gradient ascent. In International Conference on Machine Learning, pages 928-936, 2003.
    • (2003) International Conference on Machine Learning , pp. 928-936
    • Zinkevich, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.