Learning in experimental 2×2 games

Sebastian J. Goerg (), Thorsten Chmura () and Reinhard Selten

Bonn Econ Discussion Papers from University of Bonn, Germany

Abstract: In this paper we introduce four new learning models: impulse balance learning, impulse matching learning, action-sampling learning, and payoff-sampling learning. With this models and together with the models of self- tuning EWA learning and reinforcement learning, we conduct simulations over 12 different 2×2 games and compare the results with experimental data obtained by Selten & Chmura (2008). Our results are two-fold: While the simulations, especially those with action-sampling learning and impulse matching learning successfully replicate the experimental data on the aggregate, they fail in describing the individual behavior. A simple inertia rule beats the learning models in describing individuals behavior.

Keywords: Learning; Action-sampling; Payo?-sampling; Impulse balance; Impulse matching; Reinforcement; self-tuning EWA; 2×2 games; Experimental data (search for similar items in EconPapers)
JEL-codes: C72 C91 C92 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cbe, nep-cmp, nep-evo, nep-exp, nep-gth and nep-mic
Date: 2008-12

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Persistent link: http://EconPapers.repec.org/RePEc:bon:bonedp:bgse18_2008

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