Journal of System Simulation
Abstract
Abstract: In order to improve the efficiency of combat simulation, this paper provided a theoretical reference for the research on the intelligent generation of combat simulation scenarios. It systematically reviewed the intelligent generation methods of combat simulation scenarios based on large language models (LLMs). It began by introducing the basic content of combat simulation scenarios, analyzed the shortcomings of current mainstream scenario generation methods, and discussed how to leverage LLMs to address these issues. Next, it outlined the application paradigms and key supporting technologies for the intelligent generation of combat simulation scenarios based on LLMs. Finally, it pointed out the research prospects of intelligent generation of combat simulation scenarios by considering both the trends in LLMs and the demands of combat simulation.
Recommended Citation
Dong, Zhiming; Hu, Zhongqi; Liu, Zhaoyang; and Zhou, Heyang
(2025)
"A Review of Intelligent Generation of Combat Simulation Scenarios,"
Journal of System Simulation: Vol. 37:
Iss.
7, Article 6.
DOI: 10.16182/j.issn1004731x.joss.25-0032
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss7/6
First Page
1665
Last Page
1683
CLC
TP 391.9
Recommended Citation
Dong Zhiming, Hu Zhongqi, Liu Zhaoyang, et al. A Review of Intelligent Generation of Combat Simulation Scenarios[J]. Journal of System Simulation, 2025, 37(7): 1665-1683.
DOI
10.16182/j.issn1004731x.joss.25-0032
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