Network Games with Large Populations: Non-uniqueness and Learning Dynamics

Explore a 54-minute seminar on dynamic games and applications focusing on network games with large populations. Delve into the challenges of understanding and regulating network interactions in socio-economic settings involving billions of users. Examine the feasibility of collecting statistical information to infer random graph models when exact network data is unavailable. Investigate whether knowledge of such models is sufficient to infer relevant features of realized networks or control evolving dynamical processes. Learn about recent developments in convergence theory for graphon games with multiple equilibria and algorithms for learning in time-varying settings. Gain insights from Francesca Parise of Cornell University on improving efficiency, resilience, and welfare in large-scale networked systems.

Network games with large populations: non-uniqueness and learning dynamics, Francesca Parise