📄 中文摘要
强化学习（RL）因其在多种动态系统中的适应性以及在不同约束下最大化长期结果的能力，近年来被应用于传染病控制，以优化干预策略，控制传染病传播并应对疫情。RL在帮助公共卫生部门预防和控制传染病方面的潜力逐渐显现，相关于COVID-19及其他传染病的研究文献迅速增加。然而，专门讨论这一主题的综述文章相对较少，特别是针对优化非药物干预策略的RL方法的发展与应用的研究仍需进一步深入探索。
赋能疫情响应：强化学习在传染病控制中的作用
📄 English Summary
Empowering Epidemic Response: The Role of Reinforcement Learning in Infectious Disease Control
Reinforcement learning (RL) has been increasingly applied in infectious disease control to optimize intervention strategies aimed at controlling the spread of infectious diseases and responding to outbreaks. Its adaptability to various dynamic systems and the ability to maximize long-term outcomes under different constraints make it a valuable tool for public health sectors. The potential of RL in assisting with the prevention and control of infectious diseases is becoming more evident, as reflected in the growing number of publications related to COVID-19 and other infectious diseases. However, there is a lack of comprehensive surveys that focus exclusively on the development and application of RL approaches for optimizing non-pharmaceutical intervention strategies.