现代防御技术2026，Vol.54Issue(3)：93-103,11.DOI:10.3969/j.issn.1009-086x.2026.03.009
无人作战飞机超视距空战博弈对抗决策仿真
Simulation of Game-Theoretic Decision-Making for Beyond-Visual-Range Combat with UCAVs
史桐雨 1王昊 2王酉琨 1吕茂隆1
作者信息
- 1. 空军工程大学 空管领航学院,陕西 西安 710051
- 2. 军事科学院 军事智能研究院,北京 100091
- 折叠
摘要
Abstract
Reinforcement learning(RL)performance in beyond-visual-range(BVR)air combat is constrained by inadequate training opponents.This paper proposes a rule-based agent decision framework serving as RL training adversaries,where simulations confirm significantly enhanced combat effectiveness through efficient mastery of tactical maneuvers and improved adaptive decision-making.Fundamental aircraft maneuvers are modeled within an air combat simulation environment with collaborative strategy training modules.To address incomplete coverage and complexity in conventional rule-based decision trees,a state-machine-driven framework implements event-condition mechanisms for state transitions and combat decisions,demonstrating superior performance in comparative simulations.Finally,RL agents trained against this state-machine-based opponent under expert knowledge guidance autonomously acquire classical maneuvers while exhibiting advanced decision adaptability,providing foundational insights for BVR decision systems.关键词
超视距空战/无人机/自主决策/基于规则的决策/强化学习/专家知识Key words
beyond visual range air combat/unmanned aerial vehicle(UAV)/independent decision making/rule based decision making/reinforcement learning/expert domain knowledge分类
军事科技引用本文复制引用
史桐雨,王昊,王酉琨,吕茂隆..无人作战飞机超视距空战博弈对抗决策仿真[J].现代防御技术,2026,54(3):93-103,11.
