摘要
针对防空编队智能部署方法无法同时兼顾区域掩护和目标掩护、人为制定复杂规则难以求解、算法执行效率较低的问题,提出一种基于独立多智能体近端策略优化(IN-MAPPO)的防空编队部署方法。设计独立的行动者-评论家网络,以适应火力单元的不同角色,通过集中式价值函数和奖励函数促进火力单元协同合作完成混合部署任务,提高编队的抗击能力和整体部署性能。实验结果表明:IN-MAPPO方法能够依据智能体的角色完成混合部署任务,提高远程火力单元的抗击能力,比其他MAPPO算法减少了13.7%的训练时间;与现有智能算法相比,火力单元覆盖面积提升了4.2%,有效掩护宽度提升了12.3%,算法的执行效率提高了95.9%。
Aiming at the problems that the intelligent deployment method of air defense formations cannot take into account both regional cover and target cover at the same time,the artificially formulated complex rules are difficult to solve,and the algorithm execution efficiency is low,an air defense formation deployment method based on Independent Multi-Agent Proximal Policy Optimization(IN-MAPPO)is proposed.An independent actor-critic network is designed to adapt to the different roles of fire units.It promotes the collaborative cooperation of fire units to complete hybrid deployment tasks through centralized value functions and reward functions,and improves the resistance capability and the overall deployment performance of the formation.Experimental results show that IN-MAPPO can complete the mixed deployment tasks according to the role of the agent,improve the resistance capability of remote fire units,and reduce the training time by 13.7%compared with other MAPPO algorithms.Compared with existing intelligent algorithms,the coverage area of fire units is increased by 4.2%,the effective cover width is increased by 12.3%,and the execution efficiency of the algorithm increased by 95.9%.
作者
简泽民
申国伟
刘莉
王美琪
JIAN Zemin;SHEN Guowei;LIU Li;WANG Meiqi(State Key Laboratory of Public Big Data,College of Computer Science&Technology,Guizhou University,Guiyang 550000,China;JiangNan Design&Research Institute of Machinery&Electricity,Guiyang 550000,China)
出处
《电光与控制》
CSCD
北大核心
2024年第12期91-97,共7页
Electronics Optics & Control
基金
黔科合平台人才-CXTD[2021]003。
