Work

Pandemic Control, Game Theory and Machine Learning

Year: 2022

Type: preprint

Abstract: Game theory has been an effective tool in the control of disease spread and in suggesting optimal policies at both individual and area levels. In this AMS Notices article, we focus on the decision-making development for the intervention of COVID-19, aiming to provide mathematical models and efficient machine learning methods, and justifications for related policies that have been implemented in the past and explain how the authorities' decisions affect their neighboring regions from a game theory viewpoint.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2208.08646

Authors: Xuan, Yao, Balkin, Robert, Han, Jiequn, Hu, Ruimeng, Ceniceros, Hector D.

Institution: University of California, Santa Barbara

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Science Foundation