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Learning in experimental 2×2 games

Thorsten Chmura (), Sebastian Goerg and Reinhard Selten

No 18/2008, Bonn Econ Discussion Papers from University of Bonn, Bonn Graduate School of Economics (BGSE)

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; Payoff-sampling; Impulse balance; Impulse matching; Reinforcement; self-tuning EWA; 2 x 2 games; Experimental data (search for similar items in EconPapers)
JEL-codes: C72 C91 C92 (search for similar items in EconPapers)
Date: 2008
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https://www.econstor.eu/bitstream/10419/37045/1/603340342.pdf (application/pdf)

Related works:
Journal Article: Learning in experimental 2×2 games (2012) Downloads
Working Paper: Learning in experimental 2 x 2 games (2011) Downloads
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