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Stochastic Game Theory: Adjustment to Equilibrium Under Noisy Directional Learning

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Author Info

  • Simon P. Anderson

    ()

  • Jacob K. Goeree

    ()

  • Charles A. Holt

    ()

Abstract

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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File URL: http://www.virginia.edu/economics/RePEc/vir/virpap/papers/virpap327.pdf
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Bibliographic Info

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 1999
Date of revision:
Handle: RePEc:vir:virpap:327

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Web page: http://www.virginia.edu/economics/home.html

Related research

Keywords: bounded rationality; noisy directional learning; Fokker- Planck equation; potential games; logit equilibrium; stochastic potential.;

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References

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  12. A. Roth & I. Er’ev, 2010. "Learning in Extensive Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Run," Levine's Working Paper Archive 387, David K. Levine.
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  1. Article Summary: Noisy Directional Learning and the Logit Equilibrium
    by John Barrdear in John Barrdear on 2009-08-24 13:38:19
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