Independent Soft Actor‐Critic Deep Reinforcement Learning for UAV Cooperative Air Combat Maneuvering Decision‐Making

ABSTRACT This paper delves into the research of collaborative combat strategies for multiple unmanned combat aerial vehicles (UAVs), utilizing the independent soft Actor‐Critic (is‐AC) algorithm. We aim to achieve collaborative jamming confrontation, accurate battlefield situational awareness, and UAV decision‐making capabilities to control their behavior. However, the SAC algorithm is plagued by instability and poor scalability in Multi‐agent reinforcement learning scenarios. To address this, we draw inspiration from the Independent Q‐Learning (IQL) algorithm and improve SAC. Our experimental analysis of the is‐AC algorithm in UAV confrontation models demonstrates its stability and scalability in multi‐machine scenarios.