https://scholars.lib.ntu.edu.tw/handle/123456789/625032
Title: | Optimal Bayesian strategies for the infinite-armed Bernoulli bandit | Authors: | Hung Y.-C. YING-CHAO HUNG |
Keywords: | Bandit problem; Bayesian strategy; Bernoulli arms; Prior distribution | Issue Date: | 2012 | Journal Volume: | 142 | Journal Issue: | 1 | Start page/Pages: | 86-94 | Source: | Journal of Statistical Planning and Inference | 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. © 2011 Elsevier B.V. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052283185&doi=10.1016%2fj.jspi.2011.06.026&partnerID=40&md5=89933d450e514294dcb204de0b734482 https://scholars.lib.ntu.edu.tw/handle/123456789/625032 |
ISSN: | 03783758 | DOI: | 10.1016/j.jspi.2011.06.026 |
Appears in Collections: | 工業工程學研究所 |
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