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    題名: A note on infinite-armed Bernoulli bandit problems with generalized beta prior distributions
    作者: 陳功宇;Chen, Kung-yu;林千代;Lin, Chien-tai
    貢獻者: 淡江大學數學學系
    關鍵詞: Dynamic allocation of Bernoulli processes;k-failure strategy;m-run strategy;N-learning strategy;Non-recalling m-run strategy;Sequential experimentation
    日期: 2005-01
    上傳時間: 2010-01-28 07:36:45 (UTC+8)
    出版者: Springer
    摘要: A bandit problem with infinitely many Bernoulli arms is considered. The parameters of Bernoulli arms are independent and identically distributed random variables from a generalized beta distributionG3B(a, b, λ) witha, b>0 and 0<λ<2. Under the generalized beta prior distributions, we first derive the asymptotic expected failure rates ofk-failure strategies, and then obtain a lower bound for the expected failure rate over all strategies investigated in Berry et al. (1997). The asymptotic expected failure rates for the other three strategies studied in Berry et al. (1997) are also included. Numerical estimations for a variety of generalized beta prior distributions are presented to illustrate the performances of these strategies.
    關聯: Statistical Papers 46(1), pp.129-140
    DOI: 10.1007/BF02762039
    顯示於類別:[數學學系暨研究所] 期刊論文


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