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Economic Value of EWA Lite: A Functional Theory of Learning in Games

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Author Info
Ho, Teck-Hua
Camerer, Colin F.
Chong, Juin-Kuan

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Abstract

EWA Lite is a one-parameter theory of learning in normal-form games. It approximates the free parameters in an earlier model (EWA) with functions of experience. The theory is tested on seven different games and compared to other learning and equilibrium theories. Either EWA Lite or parameterized EWA predict best, but one kind of reinforcement learning predicts well in games with mixed-strategy equilibrium. Belief learning models fit worst. The economic value of theories is measured by howmuch more subjects would have earned if they followed theory recommendations. EWA Lite and EWA add the most economic value in every game but one.

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File URL: http://www.hss.caltech.edu/SSPapers/wp1122.pdf
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Publisher Info
Paper provided by California Institute of Technology, Division of the Humanities and Social Sciences in its series Working Papers with number 1122.

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Length: 54 pages
Date of creation: May 2001
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Publication status: Published:
Handle: RePEc:clt:sswopa:1122

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Postal: Working Paper Assistant, Division of the Humanities and Social Sciences, 228-77, Caltech, Pasadena CA 91125
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Postal: Working Paper Assistant, Division of the Humanities and Social Sciences, 228-77, Caltech, Pasadena CA 91125
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  1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May. [Downloadable!] (restricted)
  2. Pratt, John W & Wise, David A & Zeckhauser, Richard, 1979. "Price Differences in Almost Competitive Markets," The Quarterly Journal of Economics, MIT Press, vol. 93(2), pages 189-211, May. [Downloadable!] (restricted)
  3. Camerer, Colin F. & Ho, Tech H., 2000. "Strategic Learning and Teaching," Working Papers 1100, California Institute of Technology, Division of the Humanities and Social Sciences. [Downloadable!]
  4. Erev, Ido & Bereby-Meyer, Yoella & Roth, Alvin E., 1999. "The effect of adding a constant to all payoffs: experimental investigation, and implications for reinforcement learning models," Journal of Economic Behavior & Organization, Elsevier, vol. 39(1), pages 111-128, May. [Downloadable!] (restricted)
  5. David Cooper & John Kagel, 2008. "Learning and transfer in signaling games," Economic Theory, Springer, vol. 34(3), pages 415-439, March. [Downloadable!] (restricted)
  6. Samuelson, William & Zeckhauser, Richard, 1988. " Status Quo Bias in Decision Making," Journal of Risk and Uncertainty, Springer, vol. 1(1), pages 7-59, March.
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  1. John Duffy, 2004. "Agent-Based Models and Human Subject Experiments," Computational Economics 0412001, EconWPA. [Downloadable!]
    Other versions:
  2. Francesco Feri & Bernd Irlenbusch & Matthias Sutter, 2009. "Efficiency Gains from Team-Based Coordination – Large-Scale Experimental Evidence," Working Paper Series of the Max Planck Institute for Research on Collective Goods 2009_14, Max Planck Institute for Research on Collective Goods. [Downloadable!]
    Other versions:
  3. Yan Chen & Robert Gazzale, 2004. "When Does Learning in Games Generate Convergence to Nash Equilibria? The Role of Supermodularity in an Experimental Setting," American Economic Review, American Economic Association, vol. 94(5), pages 1505-1535, December. [Downloadable!]
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