TY - GEN
T1 - Modeling Presymptomatic Spread in Epidemics via Mean-Field Games
AU - Olmez, S. Yagiz
AU - Aggarwal, Shubham
AU - Kim, Jin Won
AU - Miehling, Erik
AU - Basar, Tamer
AU - West, Matthew
AU - Mehta, Prashant Girdharilal
N1 - Funding Information:
Research supported in part by the C3.ai Digital Transformation Institute sponsored by C3.ai Inc. and the Microsoft Corporation and in part by the National Science Foundation grants NSF-ECCS 20-32321 and NSF-CMMI 1761622.
Publisher Copyright:
© 2022 American Automatic Control Council.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.23919/ACC53348.2022.9867547
DO - 10.23919/ACC53348.2022.9867547
M3 - Conference contribution
AN - SCOPUS:85138493500
T3 - Proceedings of the American Control Conference
SP - 3648
EP - 3655
BT - 2022 American Control Conference, ACC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 American Control Conference, ACC 2022
Y2 - 8 June 2022 through 10 June 2022
ER -