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Understanding the evolution of human social systems requires flexibleformalisms for the emergence of institutions. Although game theory is normallyused to model interactions individually, larger spaces of games can be helpfulfor modeling how interactions change. We introduce a framework for modeling"institutional evolution," how individuals change the games they are placed in.We contrast this with the more familiar within-game "behavioral evolution".Starting from an initial game, agents trace trajectories through game space byrepeatedly navigating to more preferable games until they converge on attractorgames that are preferred to all others. Agents choose between games on thebasis of their "institutional preferences," which define between-gamecomparisons in terms of game-level features such as stability, fairness, andefficiency. Computing institutional change trajectories over the two-playerspace, we find that the attractors of self-interested economic agentsover-represent fairness by 100% relative to baseline, even though those agentsare indifferent to fairness. This seems to occur because fairness, as a gamefeature, co-occurs with the self-serving features these agents do prefer. Wethus present institutional evolution as a mechanism for encouraging thespontaneous emergence of cooperation among inherently selfish agents. We thenextend these findings beyond two players, and to two other types ofevolutionary agent: the relative fitness maximizing agent of evolutionary gametheory (who maximizes inequality), and the relative group fitness maximizingagent of multi-level/group selection theory (who minimizes inequality). Thiswork provides a flexible, testable formalism for modeling the interdependenciesof behavioral and institutional evolutionary processes.

A dynamic over games drives selfish agents to win-win outcomes