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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/61596
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/61596

    Title: Optimal Bayesian Strategies for the Infinite-armed Bernoulli Bandit
    Authors: 洪英超
    Contributors: 統計系
    Keywords: Bandit problem;Bernoulli arms;Bayesian strategy;Prior distribution
    Date: 2012.01
    Issue Date: 2013-11-11 17:42:24 (UTC+8)
    Abstract: We consider the bandit problem with an infinite number of Bernoulli arms, of which the unknown parameters are assumed to be i.i.d. random variables with a common distribution F. Our goal is to construct optimal strategies of choosing “arms” so that the expected long-run failure rate is minimized. We first review a class of strategies and establish their asymptotic properties when F is known. Based on the results, we propose a new strategy and prove that it is asymptotically optimal when F is unknown. Finally, we show that the proposed strategy performs well for a number of simulation scenarios.
    Relation: Journal of Statistical Planning and Inference, 142, 86-94
    Data Type: article
    DOI 連結: http://dx.doi.org/http://dx.doi.org/10.1016/j.jspi.2011.06.026
    DOI: 10.1016/j.jspi.2011.06.026
    Appears in Collections:[統計學系] 期刊論文

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