Evidence for Learning to Learn Behavior in Normal Form Games
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
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- Martin Posch, 1997. "Win Stay---Lose Shift: An Elementary Learning Rule for Normal Form Games," Research in Economics 97-06-056e, Santa Fe Institute.
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- Foster, Dean P. & Young, H. Peyton, 2003.
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- Dean Foster & Peyton Young, . "Learning with Hazy Beliefs," ELSE working papers 023, ESRC Centre on Economics Learning and Social Evolution.
- 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.
- Dale O. Stahl, 1999. "Evidence based rules and learning in symmetric normal-form games," International Journal of Game Theory, Springer, vol. 28(1), pages 111-130.
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