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Social Learning in One-Arm Bandit Problems

Abstract : We study a two-player one-arm bandit problem in discrete time, in which the risky arm can have two possible types, high and low, the decision to stop experimenting is irreversible, and players observe each other's actions but not each other's payoffs. We prove that all equilibria are in cutoff strategies and provide several qualitative results on the sequence of cutoffs.
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Contributor : Antoine Haldemann Connect in order to contact the contributor
Submitted on : Wednesday, March 17, 2010 - 3:43:20 PM
Last modification on : Wednesday, October 27, 2021 - 2:55:33 PM


  • HAL Id : hal-00464609, version 1


Nicolas Vieille, Dinah Rosenberg, Eilon Solan. Social Learning in One-Arm Bandit Problems. Econometrica, Econometric Society, 2007, Vol.75,n°6, pp.1591-1611. ⟨hal-00464609⟩



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