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The Logit-Response Dynamics

Carlos Alós-Ferrer and Nick Netzer

No 28, TWI Research Paper Series from Thurgauer Wirtschaftsinstitut, Universität Konstanz

Abstract: We develop a characterization of stochastically stable states for the logit-response learning dynamics in games, with arbitrary specification of revision opportunities. The result allows us to show convergence to the set of Nash equilibria in the class of best-response potential games and the failure of the dynamics to select potential maximizers beyond the class of exact potential games. We also study to which extent equilibrium selection is robust to the specification of revision opportunities. Our techniques can be extended and applied to a wide class of learning dynamics in games.

Keywords: Learning in games; logit-response dynamics; best-response potential games (search for similar items in EconPapers)
Date: 2008
New Economics Papers: this item is included in nep-gth
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Citations: View citations in EconPapers (2)

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Journal Article: The logit-response dynamics (2010) Downloads
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