Title: Equilibria, information and frustration in heterogeneous network games with conflicting preferences,
Abstract: Interactions between people are the basis on which the structure of our
society arises as a complex system and, at the same time, are the starting
point of any physical description of it. In the last few years, much
theoretical research has addressed this issue by combining the physics of
complex networks with a description of interactions in terms of evolutionary
game theory. We here take this research a step further by introducing a most
salient societal factor such as the individuals' preferences, a characteristic
that is key to understand much of the social phenomenology these days. We
consider a heterogeneous, agent-based model in which agents interact
strategically with their neighbors but their preferences and payoffs for the
possible actions differ. We study how such a heterogeneous network behaves
under evolutionary dynamics and different strategic interactions, namely
coordination games and best shot games. With this model we study the emergence
of the equilibria predicted analytically in random graphs under best response
dynamics, and we extend this test to unexplored contexts like proportional
imitation and scale free networks. We show that some theoretically predicted
equilibria do not arise in simulations with incomplete Information, and we
demonstrate the importance of the graph topology and the payoff function
parameters for some games. Finally, we discuss our results with available
experimental evidence on coordination games, showing that our model agrees
better with the experiment that standard economic theories, and draw hints as
to how to maximize social efficiency in situations of conflicting preferences.