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The Logit-Response Dynamics

  • Carlos Alos-Ferrer
  • Nick Netzer

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.

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Paper provided by Thurgauer Wirtschaftsinstitut, Universit�t Konstanz in its series TWI Research Paper Series with number 28.

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Date of creation: 2008
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Handle: RePEc:twi:respas:0028
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