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Evidence for Learning to Learn Behavior in Normal Form Games

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  • Timothy Salmon

Abstract

Evidence presented in Salmon (2001; Econometrica 69(6) 1597) indicates that typical tests to identify learning behavior in experiments involving normal form games possess little power to reject incorrect models. This paper begins by presenting results from an experiment designed to gather alternative data to overcome this problem. The results from these experiments indicate support for a learning-to-learn or rule learning hypothesis in which subjects change their decision rule over time. These results are then used to construct an adaptive learning model which is intended to mimic more accurately the behavior observed. The final section of the paper presents results from a simple simulation based analysis comparing the performance of this adaptive learning model with that of several standard decision rules in reproducing the choice patterns observed in the experiment. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Timothy Salmon, 2004. "Evidence for Learning to Learn Behavior in Normal Form Games," Theory and Decision, Springer, vol. 56(4), pages 367-404, April.
    • Handle: RePEc:kap:theord:v:56:y:2004:i:4:p:367-404
    DOI: 10.1007/s11238-004-8736-2
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    References listed on IDEAS

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    1. Sergiu Hart & Andreu Mas-Colell, 2013. "A Simple Adaptive Procedure Leading To Correlated Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 2, pages 17-46, World Scientific Publishing Co. Pte. Ltd..
    2. Dean Foster & Peyton Young, "undated". "Learning with Hazy Beliefs," ELSE working papers 023, ESRC Centre on Economics Learning and Social Evolution.
    3. Dale O. Stahl, 1999. "Evidence based rules and learning in symmetric normal-form games," International Journal of Game Theory, Springer;Game Theory Society, vol. 28(1), pages 111-130.
    4. Nathaniel T Wilcox, 2003. "Heterogeneity and Learning Principles," Levine's Bibliography 666156000000000435, UCLA Department of Economics.
    5. Foster, Dean P. & Young, H. Peyton, 2003. "Learning, hypothesis testing, and Nash equilibrium," Games and Economic Behavior, Elsevier, vol. 45(1), pages 73-96, October.
    6. Martin Posch, 1997. "Win Stay---Lose Shift: An Elementary Learning Rule for Normal Form Games," Research in Economics 97-06-056e, Santa Fe Institute.
    7. Shachat, Jason & Walker, Mark, 2004. "Unobserved heterogeneity and equilibrium: an experimental study of Bayesian and adaptive learning in normal form games," Journal of Economic Theory, Elsevier, vol. 114(2), pages 280-309, February.
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    Cited by:

    1. Asim Ansari & Ricardo Montoya & Oded Netzer, 2012. "Dynamic learning in behavioral games: A hidden Markov mixture of experts approach," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 475-503, December.
    2. Teck H Ho & Colin Camerer & Juin-Kuan Chong, 2003. "Functional EWA: A one-parameter theory of learning in games," Levine's Working Paper Archive 506439000000000514, David K. Levine.
    3. Wen, Yuanji, 2018. "Voluntary information acquisition in an asymmetric-Information game:comparing learning theories in the laboratory," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 202-219.

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