航空兵器2025，Vol.32Issue(2)：19-33,15.DOI:10.12132/ISSN.1673-5048.2024.0167
多无人机空战机动决策中的深度强化学习:实践中的关键技术综述与未来展望
Deep Reinforcement Learning in Multi-UAV Air Combat Maneuver Decision-Making:A Review of Key Techniques in Practice and Future Prospects
方思雨 1张振华 2牛经龙 2边疆 2徐昌一 1吴玉虎1
作者信息
- 1. 大连理工大学控制科学与工程学院,辽宁大连 116024
- 2. 北方自动控制技术研究所,太原 030006
- 折叠
摘要
Abstract
The technology of deep reinforcement learning-based multi-UAV air combat maneuver decision-making is a hot research area in modern military studies.By combining the advantages of deep learning in han-dling high-dimensional complex data and the advantages of reinforcement learning in autonomous long-term plan-ning,intelligent behaviors for air combat maneuver decision-making emerge.Aimed at providing practical opti-mization suggestions or basic entry-level guidance for researchers in this field,this paper focuses on the key technologies involved in multi-UAV air combat from a practical perspective,including improvements in deep re-inforcement learning algorithms,the design of efficient training methods,and the construction of multi-UAV combat environments.The paper introduces and summarizes current mainstream methods and innovative techno-logical achievements of them.Finally,it discusses future key research directions:centering on multi-agent col-laborative combat for UAV swarms,focusing on the evaluation and construction of air combat scenarios in real battlefield environments,and developing comprehensive intelligent decision-making systems based on diverse de-cision-making methods.These developments are of significant importance for modern air combat advancements and achieving air combat superiority.关键词
无人机/空战/机动决策/深度强化学习/多智能体协同Key words
UAV/air combat/maneuver decision-making/deep reinforcement learning/multi-agent col-laboration分类
武器工业引用本文复制引用
方思雨,张振华,牛经龙,边疆,徐昌一,吴玉虎..多无人机空战机动决策中的深度强化学习:实践中的关键技术综述与未来展望[J].航空兵器,2025,32(2):19-33,15.
