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The Logit-Response Dynamics

Author

Listed:
  • Carlos Alos-Ferrer
  • Nick Netzer
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.

Suggested Citation

  • Carlos Alos-Ferrer & Nick Netzer, 2008. "The Logit-Response Dynamics," TWI Research Paper Series 28, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    • Handle: RePEc:twi:respas:0028
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    References listed on IDEAS

    as
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    Keywords

    Learning in games; logit-response dynamics; best-response potential games;
    All these keywords.

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