English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 49633/84879 (58%)
造訪人次 : 7694340      線上人數 : 62
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41450

    題名: Some optimal strategies for bandit problems with beta prior distributions
    作者: 林千代;Lin, Chien-tai;Shiau, C. J.
    貢獻者: 淡江大學數學學系
    關鍵詞: Bandit problems;sequential experimentation;dynamic allocation of Bernoulli processes;staying-with-a-winner;switching-on-a-loser;k-failure strategy;m-run strategy;non-recalling m-run strategy;N-learning strategy
    日期: 2000-06-01
    上傳時間: 2010-01-28 07:35:53 (UTC+8)
    出版者: Kluwer Academic Publishers
    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 common distribution with beta(a, b). We investigate the k-failure strategy which is a modification of Robbins's stay-with-a-winner/switch-on-a-loser strategy and three other strategies proposed recently by Berry et al. (1997, Ann. Statist., 25, 2103–2116). We show that the k-failure strategy performs poorly when b is greater than 1, and the best strategy among the k-failure strategies is the 1-failure strategy when b is less than or equal to 1. Utilizing the formulas derived by Berry et al. (1997), we obtain the asymptotic expected failure rates of these three strategies for beta prior distributions. Numerical estimations and simulations for a variety of beta prior distributions are presented to illustrate the performances of these strategies.

    Bandit problemssequential experimentationdynamic allocation of Bernoulli processesstaying-with-a-winnerswitching-on-a-loserk-failure strategym-run strategynon-recalling m-run strategyN-learning strategy
    關聯: Annals of the Institute of Statistical Mathematics 52(2), pp.397-405
    DOI: 10.1023/A:1004130209258
    顯示於類別:[數學學系暨研究所] 期刊論文


    檔案 描述 大小格式瀏覽次數



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋