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博弈对抗驱动的杀伤网设计策略大空间探索与方案优化

李传浩1,明振军1,2*,王国新1,2,阎艳1,2,万斯来1,陈刚1,秦琳浩1   

  1. 1.北京理工大学 机械与车辆学院;2.北京理工大学长三角研究院(嘉兴)
  • 收稿日期:2025-06-06 修回日期:2025-08-18
  • 基金资助:
    国家自然科学基金项目(62373047)

Large Space Strategy Exploration and Scheme Optimization of Kill-Web Design Strategy Driven by Game Confrontation

LI Chuanhao 1,MING Zhenjun 1,2*,WANG Guoxin1,2,YAN Yan1,2,WAN Silai1,CHEN Gang1,QIN Linhao1   

  1. 1. School of Mechanical Engineering, Beijing Institute of Technology; 2. Yangtze Delta Region Academy of Beijing Institute of Technology
  • Received:2025-06-06 Revised:2025-08-18

摘要: 针对现有基于单边优化的杀伤网设计方法在博弈对抗中方案有效性不足,以及博弈机制引入后因策略空间巨大导致的求解瓶颈问题,提出一种博弈对抗驱动的杀伤网设计大空间策略探索与方案优化方法。为实现杀伤网博弈对抗的有效建模,结合观察、判断、决策和行动循环理论,考虑侦察、指控和打击三类装备,设计了杀伤网博弈的策略空间与策略约束,引入敌方打击行为导致装备精度削弱进而降低作战效能的机制量化博弈对双方收益的影响,从而建立杀伤网设计的矩阵博弈模型;针对该模型中双方策略空间规模巨大,导致传统博弈求解方法难以实现方案的高效探索与优化的问题,设计了一种基于模拟退火改进的双重预言算法,该算法融合了双重预言算法的策略池迭代机制与模拟退火算法的全局搜索能力,能够有效探索大空间博弈中的混合策略纳什均衡,进行杀伤网设计方案的高效优化。案例验证结果表明,所提方法能够实现博弈对抗场景下杀伤网设计最优方案的高效求解,相比传统单边优化算法显著提升了策略期望收益,为实际体系对抗中的杀伤网设计提供了理论支持和决策依据。

关键词: 杀伤网, 博弈对抗, 设计空间探索, 博弈论, 矩阵博弈, 双重预言算法

Abstract: Aiming at the lack of effectiveness of the existing kill-web design method based on unilateral optimization in game confrontation, and the bottleneck problem caused by the huge strategy space after the introduction of game mechanism, a large space strategy exploration and scheme optimization method for killing net design driven by game confrontation is proposed. In order to effectively model the game confrontation of kill-web design, combined with OODA cycle theory, considering three types of equipment, reconnaissance, accusation and strike, the strategy space and strategy constraints of kill-web game are designed. The mechanism of enemy strike behavior leading to equipment accuracy weakening and then reducing combat effectiveness is introduced to quantify the impact of game on the revenue of both sides, so as to establish a matrix game model of kill-web design. Aiming at the problem that the strategy space of both sides in the model is huge, which makes it difficult for the traditional game solution method to realize the efficient exploration and optimization of the scheme, an Improved Double Oracle with Simulated Annealing (DO-SA) algorithm is designed. The algorithm combines the strategy pool iteration mechanism of the double oracle algorithm and the global search ability of the simulated annealing algorithm, which can effectively explore the mixed strategy Nash equilibrium in the large space game and carry out the efficient optimization of the kill-web design scheme. The case verification results show that the proposed method can realize the efficient solution of the optimal scheme of the kill-web design in the game confrontation scenario. Compared with the traditional unilateral optimization algorithm, it significantly improves the expected revenue of the strategy, and provides theoretical support and decision-making basis for the design of the kill-web in the actual system confrontation.

Key words: kill-web, game confrontation, design space exploration, game theory, matrix game, double oracle algorithm

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