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Interactions between people are the basis on which the structure of oursociety arises as a complex system and, at the same time, are the startingpoint of any physical description of it. In the last few years, muchtheoretical research has addressed this issue by combining the physics ofcomplex networks with a description of interactions in terms of evolutionarygame theory. We here take this research a step further by introducing a mostsalient societal factor such as the individuals' preferences, a characteristicthat is key to understand much of the social phenomenology these days. Weconsider a heterogeneous, agent-based model in which agents interactstrategically with their neighbors but their preferences and payoffs for thepossible actions differ. We study how such a heterogeneous network behavesunder evolutionary dynamics and different strategic interactions, namelycoordination games and best shot games. With this model we study the emergenceof the equilibria predicted analytically in random graphs under best responsedynamics, and we extend this test to unexplored contexts like proportionalimitation and scale free networks. We show that some theoretically predictedequilibria do not arise in simulations with incomplete Information, and wedemonstrate the importance of the graph topology and the payoff functionparameters for some games. Finally, we discuss our results with availableexperimental evidence on coordination games, showing that our model agreesbetter with the experiment that standard economic theories, and draw hints asto how to maximize social efficiency in situations of conflicting preferences.

Equilibria, information and frustration in heterogeneous network games with conflicting preferences