Two-Speed Evolution of Strategies and Preferences In Symmetric Games

Agents in a large population are randomly matched to play a certain game, payoffs in which represent fitness. Agents may have preferences that are different from fitness. They learn strategies according to their preferences, and evolution changes the preference distribution in the population according to fitness. When agents know the preferences of the opponent in a match, only efficient symmetric strategy profiles of the fitness game can be stable. When agents do not know the preferences of the opponent, only Nash equilibria of the fitness game can be stable. For 2 × 2 symmetric games I characterize preferences that are stable. Copyright Springer 2004