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Rule Learning in Symmetric Normal-Form Games: Theory and Evidence

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  • Dale O. Stahl

    (Eco, U. of Texas)

Abstract

We improve Stahl's (1996b) model of boundedly rational behavioral rules and rule learning for symmetric normal-form games with unique symmetric Nash equilibria. A player begins with initial propensities on a class of evidence-based behavioral rules, and given experience over time adjusts his/her propensities in proportion to the past performance of the rules. An experiment consisting of two 15 period runs with 5x5 games was designed to test this model. The experimental data provide significant support for rule learning and heterogeneity among individuals. We also strongly reject "Nash learning" and "Cournot dynamics" in favor of rule learning.

Suggested Citation

  • Dale O. Stahl, 1997. "Rule Learning in Symmetric Normal-Form Games: Theory and Evidence," CARE Working Papers 9710, The University of Texas at Austin, Center for Applied Research in Economics.
  • Handle: RePEc:tex:carewp:9710
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