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Coordination, “Magic,” and Reinforcement Learning in a Market Entry Game☆,☆☆

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Abstract

Previous experimental studies have documented quick convergence to equilibrium play in market entry games with a large number of agents. The present study examines the effect of the available information in a 12-player game in an attempt to account for these findings. In line with the prediction of a simple reinforcement learning model (Roth and Erev, 1995,Games Econ. Behav.8, 164–212), quick convergence to equilibrium is observed even given minimal information (unknown payoff rule). However, in violation of the basic model, information concerning other players' payoff increases the number of entrants. The information effect can be described by a variant of the basic reinforcement learning model assuming that the additional information changes the player's reference point.Journal of Economic LiteratureClassification Number: C7, C92.

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    ☆

    This work was supported in part by Grant 604-94-1 on market entry games from the Israel Science Foundation, awarded to Ido Erev and Amnon Rapoport, and NSF Grant SBR-95-12724, awarded to Amnon Rapoport and Kenneth Koput. The authors wish to thank Tamar Landsbeger, Einat Duvdevani, and Shmuel Bar-Shai for help in data collection and constructive comments. Part of this research was conducted when Erev was on sabbatical at the Department of Economics, University of Pittsburgh.

    ☆☆

    R. Hogarth

    †

    E-mail:[email protected].

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