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An Experimental Analysis of the Two-Armed Bandit Program

Banks, Jeffrey and Olson, Mark and Porter, David (1994) An Experimental Analysis of the Two-Armed Bandit Program. Social Science Working Paper, 892. California Institute of Technology , Pasadena, CA. (Unpublished)

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We investigate, in an experimental setting, the behavior of single decision makers who at discrete time intervals over an "infinite" horizon may choose one action from a set of possible actions where this set is constant over time, i.e. a bandit problem. Two bandit environments are examined, one in which the predicted behavior should always be myopic (the two-armed bandit) and the other in which the predicted behavior should never be myopic (the one-armed bandit). We also investigate the comparative static predictions as the underlying parameter of the bandit environments are changed. The aggregate results show that the cutpoint behavior in the two bandit environments are quantitatively different and in the direction of the theoretical predictions. Furthermore, while a significant number of individual cutpoints exhibit nonstationarity (contrary to the theory), the most likely, i.e. maximum likelihood estimates, collection of decision rules that best explain overall behavior are those that are consistent with the underlying theory.

Item Type:Report or Paper (Working Paper)
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URLURL TypeDescription ItemPublished Version
Alternate Title:An experimental analysis of the bandit problem
Additional Information:Published as Banks, Jeffrey, Mark Olson, and David Porter. "An experimental analysis of the bandit problem." Economic Theory 10, no. 1 (1997): 55-77.
Group:Social Science Working Papers
Series Name:Social Science Working Paper
Issue or Number:892
Classification Code:JEL: C91, C73, D81, D83
Record Number:CaltechAUTHORS:20170822-142127351
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:80690
Deposited By: Jacquelyn Bussone
Deposited On:23 Aug 2017 18:10
Last Modified:03 Oct 2019 18:33

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