Social Learning in One-Arm Bandit Problems.

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 strat...

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Publicado en:Econometrica Vol. 75; no. 6; pp. 1591 - 1612
Autores principales: Rosenberg, Dinah, Solan, Eilon, Vieille, Nicolas
Formato: Artículo
Publicado: Wiley-Blackwell November 2007
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: November 2007
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      pub: Wiley-Blackwell
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        10.1111/j.1468-0262.2007.00807.x
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        atl: Social Learning in One-Arm Bandit Problems.
      aug:
        au:
          Rosenberg, Dinah
          Solan, Eilon
          Vieille, Nicolas
      su:
        Social learning
        Economics
        Game theory
        Slot machines
      sug:
        subj:
          Social learning
          Economics
          Game theory
          Slot machines
      ab: 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. Reprinted by permission of the publisher.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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