Using Symbolic Regression to Infer Strategies from Experimental Data
AbstractWe 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 implementation 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 regression and we conclude by arguing that symbolic regression techniques should at least complement standard regression analyses of experimental data.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 1033.
Date of creation: 01 Mar 1999
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-07-12 (All new papers)
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