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Volumn , Issue , 2011, Pages

Multi-bandit best arm identification

Author keywords

[No Author keywords available]

Indexed keywords

ALLOCATION STRATEGY; PERFORMANCE; PROBABILITIES OF ERROR; SMALL GAPS; SYNTHETIC PROBLEM; UPPER BOUND;

EID: 85162482585     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (106)

References (13)
  • 2
    • 38149013086 scopus 로고    scopus 로고
    • Tuning bandit algorithms in stochastic environments
    • Marcus Hutter, Rocco Servedio, and Eiji Takimoto, editors, volume 4754 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg
    • Jean-YvesAudibert, RémiMunos, and Csaba Szepesvári. Tuning bandit algorithms in stochastic environments. In Marcus Hutter, Rocco Servedio, and Eiji Takimoto, editors, Algorithmic Learning Theory, volume 4754 of Lecture Notes in Computer Science, pages 150-165.Springer Berlin / Heidelberg, 2007.
    • (2007) Algorithmic Learning Theory , pp. 150-165
    • Audibert, J.-Y.1    Munos, R.2    Szepesvári, C.3
  • 3
    • 0036568025 scopus 로고    scopus 로고
    • Finite-time analysis of the multi-armed bandit problem
    • P. Auer, N. Cesa-Bianchi, and P. Fischer. Finite-time analysis of the multi-armed bandit problem. Machine Learning, 47:235-256, 2002.
    • (2002) Machine Learning , vol.47 , pp. 235-256
    • Auer, P.1    Cesa-Bianchi, N.2    Fischer, P.3
  • 6
    • 48349140736 scopus 로고    scopus 로고
    • Rollout sampling approximate policy iteration
    • C. Dimitrakakis and M. Lagoudakis. Rollout sampling approximate policy iteration. Machine Learning Journal, 72(3):157-171, 2008.
    • (2008) Machine Learning Journal , vol.72 , Issue.3 , pp. 157-171
    • Dimitrakakis, C.1    Lagoudakis, M.2
  • 7
    • 33745295134 scopus 로고    scopus 로고
    • Action elimination and stopping conditions for the multi-armed bandit and reinforcement learning problems
    • Eyal Even-Dar, ShieMannor, and YishayMansour. Action elimination and stopping conditions for the multi-armed bandit and reinforcement learning problems. Journal ofMachine Learning Research, 7:1079-1105, 2006.
    • (2006) Journal OfMachine Learning Research , vol.7 , pp. 1079-1105
    • Even-Dar, E.1    Mannor, S.2    Mansour, Y.3
  • 13


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.