Deep Reinforcement Learning (DRL) Is Used to Optimize Vaccination Strategies and Resource Allocation

The purpose of this paper is to explore the application of deep reinforcement learning (DRL) in optimizing vaccination strategies and resource allocation. By constructing a DRL-based model, we aim to address the strategy selection and resource allocation problems encountered in the vaccination process. In this study, simulation experiments were used to verify the effectiveness of the model, and the model was compared with the existing methods. The results show that the DRL model can effectively improve the efficiency of vaccination and optimize the use of resources.