Abstract

I present an experiment on learning about a game in an initially unknown environment. Subjects play repeatedly simple 2 × 2 normal-form coordination games. I compare behavioral learning algorithms for different feedback information. Minimal feedback only informs about own payoffs, while additional feedback informs about own payoffs and the opponent’s choice. Results show that minimal feedback information leads to a myopic learning algorithm, while additional feedback induces non-myopic learning and increases the impulse with which players respond to payoff differences. Finally, there is evidence for a strategy transfer across games which differ only according to the relabel of actions, but not according to permutation in the payoff matrix