A survey of deep reinforcement learning technologies for intelligent air combat

Abstract

Major aviation nations and related research institutions are focusing on exploration and research of key technologies for intelligent air combat. Deep reinforcement learning combines the perceptual ability of deep learning with the decision-making ability of reinforcement learning, demonstrating significant advantages in the emergence of air combat capabilities. Based on the urgent needs of intelligent air combat development, the points of integration with the air combat field are explored by analyzing and summarizing the mainstream algorithms in the field of deep reinforcement learning. From the perspective of algorithm implementation, the key technologies of deep reinforcement learning in air combat are pointed out. By sorting out the current cutting-edge technological achievements in the field of air combat, it is concluded that the future research on deep reinforcement learning will develop from single-to-single air combat to cluster air combat. The challenges algorithm faced are proposed, which can provide the reference and guidance for the development of intelligent algorithms in intelligent air combat.

Keywords

• intelligent air combat
• deep reinforcement learning
• combat aircraft
• key technologies
• development trend