Graphon Games

Francesca Parise (Cornell University)
https://simons.berkeley.edu/node/22610
Graph Limits, Nonparametric Models, and Estimation
Many of todays most promising technological systems involve very large numbers of autonomous agents that influence each other and make strategic decisions within a network structure. Examples include opinion dynamics, targeted marketing in social networks, economic exchange and international trade, product adoption and social contagion. While traditional tools for the analysis of these systems assumed that a social planner has full knowledge of the underlying game, when we turn to very large networks two issues emerge. First, collecting data about the exact network of interactions becomes very expensive or not at all possible because of privacy concerns. Second, methods for designing optimal interventions that rely on the exact network structure typically do not scale well with the population size.
To obviate these issues, in this talk I will consider a framework in which the social planner designs interventions based on probabilistic instead of exact information about agents interactions. I will introduce the tool of graphon games as a way to formally describe strategic interactions in this setting and I will illustrate how this tool can be exploited to design asymptotically optimal interventions for general classes of network games, beyond the linear quadratic setting.