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Man versus Nash An experiment on the self-enforcing nature of mixed strategy equilibrium

  • Jason Shachat

    ()

    (Wang Yanan Institute for Studies in Economics and MOE Key Laboratory in Econometrics, Xiamen University)

  • J. Todd Swarthout

    ()

    (Department of Economics, Georgia State University)

  • Lijia Wei

    ()

    (Wang Yanan Institute for Studies in Economics, Xiamen University)

We examine experimentally how humans behave when they play against a computer which implements its part of a mixed strategy Nash equilibrium. We consider two games, one zero-sum and another unprofitable with a pure minimax strategy. A minority of subjects’ play was consistent with their Nash equilibrium strategy, while a larger percentage of subjects’ play was more consistent with different models of play: equiprobable play for the zero-sum game, and the minimax strategy in the unprofitable game. We estimate the heterogeneity and dynamics of the subjects’ latent mixed strategy sequences via a hidden Markov model. This provides clear results on the identification of the use of pure and mixed strategies and the limiting distribution over strategies. The mixed strategy Nash equilibrium is not self-enforcing except when it coincides with the equal probability mixed strategy, and there is surprising amounts of pure strategy play and clear cycling between the pure strategy states.

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File URL: http://feel.xmu.edu.cn/RePEc/wpaper/Man_Versus_Nash.pdf
File Function: 2011
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Paper provided by Xiamen Unversity, The Wang Yanan Institute for Studies in Economics, Finance and Economics Experimental Laboratory in its series Working Papers with number 1101.

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Length: 29 pages
Date of creation: 21 Feb 2011
Date of revision: 21 Feb 2011
Handle: RePEc:fee:wpaper:1101
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Web page: http://feel.xmu.edu.cnEmail:


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  1. Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard, 2005. "Rage Against the Machines - How Subjects Learn to Play Against Computers," Sonderforschungsbereich 504 Publications 05-36, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
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  8. Jason Shachat & J. Todd Swarthout, 2013. "Learning about learning in games through experimental control of strategic interdependence," Papers 2013-10-14, Working Paper.
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  12. Steven D. Levitt & John A. List & David H. Reiley, 2010. "What Happens in the Field Stays in the Field: Exploring Whether Professionals Play Minimax in Laboratory Experiments," Econometrica, Econometric Society, vol. 78(4), pages 1413-1434, 07.
  13. Mookherjee Dilip & Sopher Barry, 1994. "Learning Behavior in an Experimental Matching Pennies Game," Games and Economic Behavior, Elsevier, vol. 7(1), pages 62-91, July.
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  16. Shachat, Jason M., 2002. "Mixed Strategy Play and the Minimax Hypothesis," Journal of Economic Theory, Elsevier, vol. 104(1), pages 189-226, May.
  17. Spiliopoulos, Leonidas, 2008. "Humans versus computer algorithms in repeated mixed strategy games," MPRA Paper 6672, University Library of Munich, Germany.
  18. Morgan, John & Sefton, Martin, 2002. "An Experimental Investigation of Unprofitable Games," Games and Economic Behavior, Elsevier, vol. 40(1), pages 123-146, July.
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  21. repec:spr:compst:v:59:y:2004:i:3:p:359-373 is not listed on IDEAS
  22. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-81, September.
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