Abstract:Aiming at the problem of combat Agent adaptability, this paper reviews the achievements of genetic algorithm, reinforcement learning, neural network and other methods in achieving combat Agent adaptability, and summarizes the characteristics of each method.It also introduces the application of deep reinforcement learning in achieving combat Agent adaptability and discusses the development trend and research focus of deep reinforcement learning in this area. This study can provide a reference for the follow-up study.