Learning in experimental 22 games - Thorsten Chmura; Sebastian J. Goerg; Reinhard Selten (University of Bonn, Bonn Graduate School of Economics (BGSE), 2008)
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 22 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: C72; C91; C92; 330; Learning; Action-sampling; Payoff-sampling; Impulse balance; Impulse matching; Reinforcement; self-tuning EWA; 2 x 2 games; Experimental data; Spieltheorie; Lernprozess; Test