  Understanding the evolution of human social systems requires flexible
formalisms for the emergence of institutions. Although game theory is normally
used to model interactions individually, larger spaces of games can be helpful
for 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 by
repeatedly navigating to more preferable games until they converge on attractor
games that are preferred to all others. Agents choose between games on the
basis of their "institutional preferences," which define between-game
comparisons in terms of game-level features such as stability, fairness, and
efficiency. Computing institutional change trajectories over the two-player
space, we find that the attractors of self-interested economic agents
over-represent fairness by 100% relative to baseline, even though those agents
are indifferent to fairness. This seems to occur because fairness, as a game
feature, co-occurs with the self-serving features these agents do prefer. We
thus present institutional evolution as a mechanism for encouraging the
spontaneous emergence of cooperation among inherently selfish agents. We then
extend these findings beyond two players, and to two other types of
evolutionary agent: the relative fitness maximizing agent of evolutionary game
theory (who maximizes inequality), and the relative group fitness maximizing
agent of multi-level/group selection theory (who minimizes inequality). This
work provides a flexible, testable formalism for modeling the interdependencies
of behavioral and institutional evolutionary processes.
