We study evolutionarily stable outcomes for a class of games that admit cooperation and conflict as possible Nash equilibria. We make use of two ideas: existing strategies are more likely to be imitated than new strategies are to be introduced; players are able to identify opponents' behavior prior to interaction. The long-run evolutionary limit is efficient for the case of perfect recognition of opponents' behavior. For the case of imperfect recognition, efficiency is not achieved and long-run outcomes are more efficient the more accurate is the information. Strategies that emerge in the long run are those where players reward opponents who are likely to play the same way, and punish opponents who are likely to play differently.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
- Evolutionary stable outcomes