Hierarchical RL with a global cost controller and local marginal-value policies outperforms RMAB and heuristic baselines by 20-30% in simulated multi-cluster SARS-CoV-2 control.
Stochastic network op- timization with application to resource allocation and queueing.Synthesis Lectures on Communication Net- works, 3:1–211
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Optimizing Resource-Constrained Non-Pharmaceutical Interventions for Multi-Cluster Outbreak Control Using Hierarchical Reinforcement Learning
Hierarchical RL with a global cost controller and local marginal-value policies outperforms RMAB and heuristic baselines by 20-30% in simulated multi-cluster SARS-CoV-2 control.