Using Symbolic Regression to Infer Strategies from Experimental Data

  • John Duffy
  • Jim Engle-Warnick
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 100)


We propose the use of a new technique—symbolic regression—as a method for inferring the strategies that are being played by subjects in economic decision-making experiments. We begin by describing symbolic regression and our implemen-tation of this technique using genetic programming. We provide a brief overview of how our algorithm works and how it can be used to uncover simple data generating functions that have the flavor of strategic rules. We then apply symbolic regression using genetic programming to experimental data from the repeated “ultimatum game.” We discuss and analyze the strategies that we uncover using symbolic re-gression and conclude by arguing that symbolic regression techniques should at least complement standard regression analyses of experimental data.


Genetic Programming Terminal Node Crossover Operation Subgame Perfect Equilibrium Ultimatum Game 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • John Duffy
    • 1
  • Jim Engle-Warnick
    • 2
  1. 1.University of PittsburghPittsburghUSA
  2. 2.Nuffield CollegeOxford UniversityOxfordUK

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