We formulate an evolutionary learning process with trembles for static games of incomplete information. For many games, if the amount of trembling is small, play will be in accordance with the games’ (strict) Bayesian equilibria most of the time. This supports the notion of Bayesian equilibrium. Often the process will select a specific equilibrium. We study an extension to incomplete information of the prototype conflict known as “Chicken” and find that the equilibrium selection by evolutionary learning may well be in favor of inefficient Bayesian equilibria where some types of players fail to coordinate. Copyright Springer-Verlag Berlin/Heidelberg 2005
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Article provided by Springer in its journal Economic Theory.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Hans Jørgen Jacobsen & Mogens Jensen & Birgitte Sloth, 1998.
"Evolutionary Learning in Signalling Games,"
CIE Discussion Papers
1999-14, University of Copenhagen. Department of Economics. Centre for Industrial Economics, revised Sep 1999.
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Hans Jørgen Jacobsen & Mogens Jensen & Birgitte Sloth, 1998.
"Evolutionary Learning in Signalling Games,"
CIE Discussion Papers
1999-14, University of Copenhagen. Department of Economics. Centre for Industrial Economics, revised Sep 1999.
[Downloadable!]
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