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Volumn 19, Issue , 2003, Pages 11-23

Learning to coordinate efficiently: A model-based approach

Author keywords

[No Author keywords available]

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; POLYNOMIALS;

EID: 4644369644     PISSN: 10769757     EISSN: 10769757     Source Type: Journal    
DOI: 10.1613/jair.1154     Document Type: Article
Times cited : (25)

References (10)
  • 2
    • 0041965975 scopus 로고    scopus 로고
    • R-max - A general polynomial time algorithm for near-optimal reinforcement learning
    • Brafman, R. I., & Tennenholtz, M. (2002). R-max - a general polynomial time algorithm for near-optimal reinforcement learning. Journal of Machine Learning Research, 3, 213-231.
    • (2002) Journal of Machine Learning Research , vol.3 , pp. 213-231
    • Brafman, R.I.1    Tennenholtz, M.2
  • 4
    • 0012251278 scopus 로고
    • On nonterminating stochastic games
    • Hoffman, A., & Karp, R. (1966). On Nonterminating Stochastic Games. Management Science, 12(5), 359-370.
    • (1966) Management Science , vol.12 , Issue.5 , pp. 359-370
    • Hoffman, A.1    Karp, R.2
  • 7
    • 85149834820 scopus 로고
    • Markov games as a framework for multi-agent reinforcement learning
    • Littman, M. L. (1994). Markov games as a framework for multi-agent reinforcement learning. In Proc. 11th Intl. Conf. on Machine Learning, pp. 157-163.
    • (1994) Proc. 11th Intl. Conf. on Machine Learning , pp. 157-163
    • Littman, M.L.1
  • 8
    • 0242466944 scopus 로고    scopus 로고
    • Friend-or-foe q-learning in general-sum games
    • Littman, M. L. (2001). Friend-or-foe q-learning in general-sum games. In Proc. ICML'01.
    • (2001) Proc. ICML'01
    • Littman, M.L.1
  • 9


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.