An Automated Generation Method for Combat Simulation Scenarios Based on Large Language Models

Authors

• Zhiming Dong, Army Arms University of PLA, Beijing 100072, China
• Zhongqi Hu, Army Arms University of PLA, Beijing 100072, China; PLA 31689 Troops
• Haoran Dai, Northern Information Control Research Institute, Nanjing 211153, China
• Jiancheng Gao, Army Arms University of PLA, Beijing 100072, China

Abstract

To address the issue of low efficiency in generating traditional army tactical combat simulation scenarios, an automated generation method based on large language models is proposed. The large language model invokes a semantic segmentation algorithm to parse and restructure the combat scenario, forming semantic modules. Utilizing a multi-agent collaborative framework based on the model contextual protocol, the large language model drives each agent to extract simulation elements from the corresponding semantic modules, constructing a knowledge graph of scenario elements. Using this knowledge graph as a retrieval medium, the method employs a dense retrieval algorithm to achieve precise matching between simulation scenario data and simulation scenario segment templates, enabling the parallel generation of simulation scenario segments. The large language model integrates these segments into a complete combat simulation scenario. In experiments conducted on a specific test set, the proposed method demonstrates significant advantages over baseline approaches in terms of scenario generation efficiency and the accuracy of scenario elements, offering a feasible practical solution for the efficient generation of combat simulation scenarios.

Recommended Citation

Dong, Zhiming; Hu, Zhongqi; Dai, Haoran; and Gao, Jiancheng (2026) "An Automated Generation Method for Combat Simulation Scenarios Based on Large Language Models," Journal of System Simulation: Vol. 38: Iss. 5, Article 1.
DOI: 10.16182/j.issn1004731x.joss.25-0966
Available at: https://dc-china-simulation.researchcommons.org/journal/vol38/iss5/1

First Page

1129

Last Page

1145

CLC

TP391.9

Recommended Citation

Dong Zhiming, Hu Zhongqi, Dai Haoran, et al. An Automated Generation Method for Combat Simulation Scenarios Based on Large Language Models[J]. Journal of System Simulation, 2026, 38(5): 1129-1145.

Corresponding Author

Hu Zhongqi

DOI

10.16182/j.issn1004731x.joss.25-0966