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Stochastic Game Theory: Adjustment to Equilibrium Under Noisy Directional Learning Author info | Abstract | Publisher info | Download info | Related research | Statistics Simon P. Anderson ()
Jacob K. Goeree ()
Charles A. Holt ()
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This paper presents a dynamic model in which agents adjust their decisions in the direction of higher payoffs, subject to random error. This process produces a probability distribution of players' decisions whose evolution over time is determined by the Fokker-Planck equation. The dynamic process is stable for all potential games, a class of payoff structures that includes several widely studied games. In equilibrium, the distributions that determine expected payoffs correspond to the distributions that arise from the logit function applied to those expected payoffs. This "logit equilibrium" forms a stochastic generalization of the Nash equilibrium and provides a possible explanation of anomalous laboratory data.
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Paper provided by University of Virginia, Department of Economics in its series Virginia Economics Online Papers with number
327.
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Length: 30 pages
Date of creation: Jul 1999Date of revision:
Handle: RePEc:vir:virpap:327Contact details of provider: Web page: http://www.virginia.edu/economics/home.html
For technical questions regarding this item, or to correct its listing, contact: (Debby Stanford).
Keywords: bounded rationality noisy directional learning Fokker- Planck equation potential games logit equilibrium stochastic potential. Other versions of this item:
Find related papers by JEL classification: C62 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Existence and Stability Conditions of Equilibrium C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
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