@article{LIU2026, 
author = {Yang LIU and Ni LI and Zexi YU and Shangjie JIA},
title = {An intelligent modeling method for aircraft formation behaviors integrating LLM technology},
year = {2026},
journal = {Acta Aeronautica et Astronautica Sinica},
volume = {47},
number = {15},
keywords = {combat simulation, aircraft formation, behavior model, hierarchical modeling framework, large language model technology},
url = {https://www.sciopen.com/article/10.7527/S1000-6893.2026.33092},
doi = {10.7527/S1000-6893.2026.33092},
abstract = {To address the complexity and high manual dependency in behavior modeling process for cooperative combat simulation scenarios, this paper integrates Large Language Model (LLM) technology to enable intelligent modeling of aircraft formation cooperative combat behaviors. A hybrid hierarchical modeling framework integrating LLM technology is proposed to enable a semantics-driven and automated modeling workflow. A two-layer ‘system-user’ prompt engineering method is designed to transform conceptual semantics into formalized state machines. A vector-retrieval-based association method is developed to achieve intelligent and efficient matching between decision states and behavior tree nodes. Based on these methods, representative cooperative combat behavior models for aircraft formations are constructed and validated through simulation experiments in typical combat scenarios. The experimental results demonstrate that the proposed framework and methods effectively support rapid and intelligent modeling of cooperative combat behaviors, confirming their applicability and practical effectiveness.}
}