Bandit Problems

Dirk Bergemann and Juuso Välimäki

No 1551, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: We survey the literature on multi-armed bandit models and their applications in economics. The multi-armed bandit problem is a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. This classic problem has received much attention in economics as it concisely models the trade-off between exploration (trying out each arm to find the best one) and exploitation (playing the arm believed to give the best payoff).

Keywords: One-Armed Bandit; Multi-Armed Bandit; Bayesian Learning; Experimentation; Index Policy; Matching; Experience Goods (search for similar items in EconPapers)
JEL-codes: C72 C73 D43 D83 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2006-01
Note: CFP 1292
References: View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Published in Steven N. Durlauf and Lawrence E. Blume, The New Palgrave Dictionary of Economics, Vol. 1, 2nd ed., Macmillan Press, 2008, pp. 336-340

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