National Science Foundation and the Malcolm Forsman Centennial Professorship, but nothing herein reflects their views.

Psychologically based rules are important in human behavior and have the potential of explaining equilibrium selection and separatrix crossings to a payoff dominant equilibrium in coordination games. We show how a rule learning theory can easily accommodate behavioral rules such as aspiration-based experimentation and reciprocity-based cooperation and how to test for the significance of additional rules. We confront this enhanced rule learning model with experimental data on games with multiple equilibria and separa-trix-crossing behavior. Maximum likelihood results do not support aspiration-based experimentation or anticipated reciprocity as significant explanatory factors, but do support a small propensity for non-aspiration-based experi-mentation by random belief and non-reciprocity-based cooperation. © 2002 Elsevier Science (USA) Key Words: aspiration; reciprocity; rules; learning; games. In recent years, the field of learning in games has evolved considerably, with recent models able to make robust predictions in a variety of interesting games