Finite State Graphon Games with Applications to Epidemics

Abstract

We consider a game for a continuum of non-identical players evolving on a finite state space. Their heterogeneous interactions are represented with a graphon, which can be viewed as the limit of a dense random graph. A player’s transition rates between the states depend on their control and the strength of interaction with the other players. We develop a rigorous mathematical framework for the game and analyze Nash equilibria. We provide a sufficient condition for a Nash equilibrium and prove existence of solutions to a continuum of fully coupled forward-backward ordinary differential equations characterizing Nash equilibria. Moreover, we propose a numerical approach based on machine learning methods and we present experimental results on different applications to compartmental models in epidemiology.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2022
Source ID
10.1007/s13235-021-00410-2

Entities

People

  • Alexander Aurell
  • Gökçe Dayanıklı
  • Mathieu Laurière
  • René Carmona

Organizations

  • Air Force Office of Scientific Research
  • Army Research Office
  • National Science Foundation

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Mathematical Modeling and Probability Theory.
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space
  • Space - Spacecraft Maneuvers