The logit-response dynamics

Carlos Alós-Ferrer; Nick Netzer

doi:10.1016/j.geb.2009.08.004

The logit-response dynamics

Carlos Alós-Ferrer, Nick Netzer

Economics

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	413-427
Number of pages	15
Journal	Games and Economic Behavior
Volume	68
Issue number	2
DOIs	https://doi.org/10.1016/j.geb.2009.08.004
State	Published - Mar 2010

Keywords

Best-response potential games
Learning in games
Logit-response dynamics

ASJC Scopus subject areas

Finance
Economics and Econometrics

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10.1016/j.geb.2009.08.004

Cite this

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title = "The logit-response dynamics",

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 = "Best-response potential games, Learning in games, Logit-response dynamics",

author = "Carlos Al{\'o}s-Ferrer and Nick Netzer",

note = "Funding Information: ✩ We thank Larry Blume, Hans Haller, Josef Hofbauer, Arthur Robson, Bill Sandholm and two anonymous referees for helpful comments. Financial support from the Austrian Science Fund (FWF) under Project P18141-G09 is gratefully acknowledged. * Corresponding author. E-mail addresses: [email protected] (C. Al{\'o}s-Ferrer), [email protected] (N. Netzer). 1 Throughout this paper, the term “Markov chain” refers to a discrete-time Markov chain with stationary transition probabilities and finite state space.",

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The logit-response dynamics

Abstract

Keywords

ASJC Scopus subject areas

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