Optimal Epidemic Control as a Contextual Combinatorial Bandit with Budget. (arXiv:2106.15808v2 [cs.LG] UPDATED)

In light of the COVID-19 pandemic, it is an open challenge and critical
practical problem to find a optimal way to dynamically prescribe the best
policies that balance both the governmental resources and epidemic control in
different countries and regions. To solve this multi-dimensional tradeoff of
exploitation and exploration, we formulate this technical challenge as a
contextual combinatorial bandit problem that jointly optimizes a multi-criteria
reward function. Given the historical daily cases in a region and the past
intervention plans …

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