自主空战连续决策方法

The future air warfare is developing in the unmanned and autonomous direction. The autonomous air war⁃ fare decision-making methods are one of the important support methods in future. Due to dimensional limitations，traditional air combat decision-making methods cannot handle continuous action and long-sighted decision-making problems. Based on the Actor-Critic method，a unified architecture for continuous decision-making in air combat is proposed in this paper. Combining air combat training experience，the state space，action space，reward and train⁃ ing subjects are rationally designed，and a variety of continuous action space reinforcement learning algorithms are tested in high uncertainty. The learning effect in the air combat scenario is visually verified. The results show that：based on the method architecture proposed in this paper，long-sighted value optimization under continuous actions can be realized，the agent can make optimal decisions in complex air combat situations，and has a high kill rate against random maneuvering flying targets. And the air combat maneuver trajectory is highly reasonable.