Individual Differences in EWA Learning with Partial Payoff Information

23 Pages Posted: 23 Dec 2007  

Teck H. Ho

affiliation not provided to SSRN

Xin Wang

affiliation not provided to SSRN

Colin Camerer

California Institute of Technology - Division of the Humanities and Social Sciences

Abstract

We extend experience-weighted attraction (EWA) learning to games in which only the set of possible foregone payoffs from unchosen strategies are known, and estimate parameters separately for each player to study heterogeneity. We assume players estimate unknown foregone payoffs from a strategy, by substituting the last payoff actually received from that strategy, by clairvoyantly guessing the actual foregone payoff, or by averaging the set of possible foregone payoffs conditional on the actual outcomes. All three assumptions improve predictive accuracy of EWA. Individual parameter estimates suggest that players cluster into two separate subgroups (which differ from traditional reinforcement and belief learning).

Suggested Citation

Ho, Teck H. and Wang, Xin and Camerer, Colin, Individual Differences in EWA Learning with Partial Payoff Information. The Economic Journal, Vol. 118, Issue 525, pp. 37-59, January 2008. Available at SSRN: https://ssrn.com/abstract=1077983 or http://dx.doi.org/10.1111/j.1468-0297.2007.02103.x

Teck H. Ho (Contact Author)

affiliation not provided to SSRN

Xin Wang

affiliation not provided to SSRN

Colin F. Camerer

California Institute of Technology - Division of the Humanities and Social Sciences ( email )

1200 East California Blvd.
Pasadena, CA 91125
United States
626-395-4054 (Phone)
626-432-1726 (Fax)

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