Design of a Multi-unmanned Aerial Vehicle Cooperative Hunting System Based on MADDPG

With their affordability, agility, and stealth capabilities, unmanned aerial vehicles (UAVs) have become indispensable assets in modern warfare. However, developing an effective UAV cooperative hunting system that can counter enemy UAV intrusions at a reasonable cost is paramount. This paper aims to tackle the challenges of autonomous cooperative decision-making among multiple UAVs within such a system. Specifically, it proposes the utilization of the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to enable cooperative hunting among multiple UAVs. The results of experiments conducted demonstrate that the MADDPG algorithm effectively facilitates efficient hunting of enemy UAVs.