We report the findings of experiments designed to study how people learn in network games. Network games offer new opportunities to identify learning rules, since on networks (compared to, e.g., random matching) more rules differ in terms of their information requirements. Our experimental...

I study the effects of improved public information on equilibrium welfare and price dispersion, providing sufficient conditions for negative and positive effects. Public information affects welfare by reducing excessive (though rational) pessimism induced by sequential learning. Reduced...

The strategic commitment moves that game theory predicts players make may sometimes seem counter-intuitive. We therefore conducted an experiment to see if people make the predicted strategic move. The experiment uses a simple bargaining situation. A player can make a strategic move of committing...

In this paper, we introduce two new learning models: impulse-matching learning and action-sampling learning. These two models together with the models of self-tuning EWA and reinforcement learning are applied to 12 different 2 x 2 games and their results are compared with the results from...

In minority games, players in a group must decide at each round which of two available options to choose, knowing that only subjects who picked the minority option obtain a positive reward. Previous experiments on the minority and similar congestion games have shown that players interacting...

This paper aspires to fill a conspicuous gap in the literature regarding learning in games — the absence of empirical verification of learning rules involving pattern recognition. Weighted fictitious play is extended to detect two-period patterns in opponents’ behavior and to comply with the...

Belief models capable of detecting 2- to 5-period patterns in repeated games by matching the current historical context to similar realizations of past play are presented. The models are implemented in a cognitive framework, ACT-R, and vary in how they implement similarity-based categorization...

We report results from an exploratory study using eye-tracking recording of information acquisition by players in a game theoretic learning paradigm. Eye-tracking is used to observe what information subjects look at in 4x4 normal-form games; the eye-tracking results favor sophisticated learning...

Substantial evidence has accumulated in recent empirical works on the limited ability of the Nash equilibrium to rationalize observed behavior in many classes of games played by experimental subjects. This realization has led to several attempts aimed at finding tractable equilibrium concepts...

In this paper, we introduce two new learning models: impulse-matching learning and action-sampling learning. These two models together with the models of self-tuning EWA and reinforcement learning are applied to 12 different 2 x 2 games and their results are compared with the results from...