智能无人蜂群作战系统适应性进化模型仿真研究  

Research on Unmanned Swarm Combat System Adaptive Evolution Model Simulation

作　　者：李志强[1] 李元龙 殷来祥 马向平 Li Zhiqiang;Li Yuanlong;Yin Laixiang;Ma Xiangping(Joint Operation Institute,National Defense University,Beijing 100091,China;Graduate School,National Defense University,Beijing 100091,China;Department of Computer,Tangshan Teachers College,Tangshan 063000,China)

机构地区：[1]国防大学联合作战学院,北京100091 [2]国防大学研究生院,北京100091 [3]唐山师范学院计算机系,河北唐山063000

出　　处：《系统仿真学报》2023年第4期878-886,共9页Journal of System Simulation

摘　　要：智能无人蜂群作战系统主要由有限行为能力的大规模作战个体组成,一般不具备应对复杂战场环境和作战对手变化的适应能力。采用遗传算法与增强学习相结合的方法探索构建基于个体的无人蜂群作战系统适应性进化模型,为了提高系统适应性进化速度,提出采用个体针对型变异优化策略改进遗传算法来提高蜂群系统的学习进化效率,在复杂系统建模仿真的SWARM平台上进行仿真实验研究,验证了本文方法的有效性。Aiming at the fact that the intelligent unmanned swarm combat system is mainly composed of large-scale combat individuals with limited behavioral capabilities and has limited ability to adapt to the changes of battlefield environment and combat opponents,a learning evolution method combining genetic algorithm and reinforcement learning is proposed to construct an individual-based unmanned bee colony combat system evolution model.To improve the adaptive evolution efficiency of bee colony combat system,an improved genetic algorithm is proposed to improve the learning and evolution speed of bee colony individuals by using individual-specific mutation optimization strategy.Simulation experiment on SWARM platform of complex system modeling and simulation verify the effectiveness of the proposed theoretical method.

关 键 词：无人蜂群 遗传算法 适应性 进化 增强学习 

分 类 号：TP949[自动化与计算机技术]