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Evolutionary Learning in the Ultimatum Game

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  • Thomas Riechmann

Abstract

The ultimatum game is (in)famous for its `anomalies': The outcomes of laboratory experiments are very different from the results generated by traditional game theory. This paper aims to find to what extent these discrepancies between theory and experiments can be explained by the effects of bounded rationality and learning dynamics. These are modeled by several agent based models and computer simulations of evolutionary learning by pure imitation as well as imitation and experiments. The main result of the analysis is surprisingly clear and robust: Proposers do not play a subgame perfect strategy but instead `learn' to make offers of about 20 to 25 % of the total amount to their opponents.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 91.

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Date of creation: 01 Apr 2001
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Handle: RePEc:sce:scecf1:91

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Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
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Keywords: ultimatum game; evolutionary dynamics; evolutionary algorithms;

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Cited by:
  1. Riechmann, Thomas, 2001. "Two Notes on Replication in Evolutionary Modelling," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Leibniz Universität Hannover dp-239, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

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