| By: |
Sebastian J. Goerg;
Thorsten Chmura;
Reinhard Selten |
| 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 |
| JEL: |
C72 C91 C92 |
| Date: |
2008–12 |
| URL: |
http://d.repec.org/n?u=RePEc:bon:bonedp:bgse18_2008&r=evo |