摘要
针对作战Agent适应性问题,梳理遗传算法、强化学习、神经网络等方法在实现作战Agent适应性方面的成果,总结每种方法的特点;介绍深度强化学习方法在实现作战Agent适应性方面的应用情况,讨论深度强化学习在该方面应用的发展趋势和研究重点。该研究可为后续相关研究提供参考。
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.
作者
王步云
刘聚
Wang Buyun;Liu Ju(Operation Software and Simulation Institute,Dalian Naval Academy,Dalian 116023,China)
出处
《兵工自动化》
2023年第9期74-78,96,共6页
Ordnance Industry Automation
