Modeling Presymptomatic Spread in Epidemics via Mean-Field Games

S. Yagiz Olmez, Shubham Aggarwal, Jin Won Kim, Erik Miehling, Tamer Basar, Matthew West, Prashant G. Mehta

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper is concerned with developing mean-field game models for the evolution of epidemics. Specifically, an agent's decision-to be socially active in the midst of an epidemic-is modeled as a mean-field game with health-related costs and activity-related rewards. By considering the fully and partially observed versions of this problem, the role of information in guiding an agent's rational decision is highlighted. The main contributions of the paper are to derive the equations for the mean-field game in both fully and partially observed settings of the problem, to present a complete analysis of the fully observed case, and to present some analytical results for the partially observed case.

Original languageEnglish (US)
Title of host publication2022 American Control Conference, ACC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781665451963
StatePublished - 2022
Event2022 American Control Conference, ACC 2022 - Atlanta, United States
Duration: Jun 8 2022Jun 10 2022

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2022 American Control Conference, ACC 2022
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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