Person:

Morris, Adam

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.

Humans often comply with social norms, but the reasons why are disputed. Here, we unify a variety of influential explanations in a common decision framework, and identify the precise cognitive variables that norms might alter to induce compliance. Specifically, we situate current theories of norm compliance within the reinforcement learning framework, which is widely used to study value-guided learning and decision-making. This framework offers an appealingly precise language to distinguish between theories, highlights the various points of convergence and divergence, and suggests novel ways in which norms might penetrate our psychology.