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Pandemic Control, Game Theory and Machine Learning. (arXiv:2208.08646v1 [math.OC])
Aug. 19, 2022, 1:10 a.m. | Yao Xuan, Robert Balkin, Jiequn Han, Ruimeng Hu, Hector D. Ceniceros
cs.LG updates on arXiv.org arxiv.org
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.
arxiv game game theory learning machine machine learning math pandemic theory
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