Observations on Cooperation

We study environments in which agents are randomly matched to play a game, and before the interaction begins each agent observes a limited amount of information about the partner's aggregate behavior. We develop a novel modeling approach for such environments and apply it to study the Prisoner's Dilemma. We first show that defection is evolutionarily stable for any level of observability and behavioral noise. Next we classify the Prisoner's Dilemma into four categories of games, and we fully characterize when cooperation is evolutionarily stable in each of them