Soft Actor-Critic Control of a Behaviorally Heterogeneous S1S2IR Epidemic Model: Stability, Bifurcation, and COVID-19 Calibration
This paper proposes a Soft Actor-Critic reinforcement learning framework integrated with a behaviorally heterogeneous S1S2IR epidemic model to dynamically optimize intervention strategies, demonstrating through COVID-19 calibration that it effectively reduces infection peaks and costs compared to static policies.