Evolution of flexibility and rigidity in retaliatory punishment.

Natural selection designs some social behaviors to depend on flexible learning processes, whereas others are relatively rigid or reflexive. What determines the balance between these two approaches? We offer a detailed case study in the context of a two-player game with antisocial behavior and retaliatory punishment. We show that each player in this game-a "thief" and a "victim"-must balance two competing strategic interests. Flexibility is valuable because it allows adaptive differentiation in the face of diverse opponents. However, it is also risky because, in competitive games, it can produce systematically suboptimal behaviors. Using a combination of evolutionary analysis, reinforcement learning simulations, and behavioral experimentation, we show that the resolution to this tension-and the adaptation of social behavior in this game-hinges on the game's learning dynamics. Our findings clarify punishment's adaptive basis, offer a case study of the evolution of social preferences, and highlight an important connection between natural selection and learning in the resolution of social conflicts.