航空科学技术2024，Vol.35Issue(4)：9-17,9.DOI:10.19452/j.issn1007-5453.2024.04.002
无人机集群对抗决策算法研究综述
Review of UAV Swarm Air-combat Decision-making Algorithms
摘要
Abstract
UAV swarm air-combat has become the development trend of future warfare,and the selection of UAV swarm air-combat decision-making algorithms is crucial for improving the UAV swarm combat ability.This paper delve into three types of UAV swarm air-combat decision-making algorithms based on rules,game theory,and neural networks,and comprehensively analyze and summarize their advantages and limitations.On this basis,this paper propose to apply the multi-agent reinforcement learning based credit assignment model and role-based malti-agent reinforcement learning model and design for UAV swarm air-combat.Finally,it emphasize the importance of selecting appropriate decision algorithms to improve the combat effectiveness of UAV clusters,and provide useful suggestions for the development of UAV countermeasures decision-making in the future,providing in-depth insights for research and application in related fields.关键词
无人机集群/博弈对抗/专家系统/博弈论/多智能体强化学习Key words
UAV swarm/air-combat/expert system/game theory/multi-agent reinforcement learning分类
航空航天引用本文复制引用
李潍,黄诗怡,刘宏明,孙张俊..无人机集群对抗决策算法研究综述[J].航空科学技术,2024,35(4):9-17,9.基金项目
航空科学基金(20200058069001) Aeronautical Science Foundation of China(20200058069001) （20200058069001）
