Research on Unmanned Swarm Combat System Adaptive Evolution Model Simulation

Authors

Zhiqiang Li, 1.Joint Operation Institute, National Defense University, Beijing 100091, China;Follow
Yuanlong Li, 2.Graduate School, National Defense University, Beijing 100091, China;
Laixiang Yin, 2.Graduate School, National Defense University, Beijing 100091, China;
Xiangping Ma, 3.Department of Computer, Tangshan Teachers College, Tangshan 063000, China;

Abstract

Abstract: 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.

Recommended Citation

Li, Zhiqiang; Li, Yuanlong; Yin, Laixiang; and Ma, Xiangping (2023) "Research on Unmanned Swarm Combat System Adaptive Evolution Model Simulation," Journal of System Simulation: Vol. 35: Iss. 4, Article 18.
DOI: 10.16182/j.issn1004731x.joss.22-FZ0893
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss4/18

First Page

878

Revised Date

2022-10-11

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.22-FZ0893

Last Page

886

CLC

TP949

Recommended Citation

Zhiqiang Li, Yuanlong Li, Laixiang Yin, Xiangping Ma. Research on Unmanned Swarm Combat System Adaptive Evolution Model Simulation[J]. Journal of System Simulation, 2023, 35(4): 878-886.

DOI

10.16182/j.issn1004731x.joss.22-FZ0893