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

LI Chuanhao; MING Zhenjun; WANG Guoxin; YAN Yan; WAN Silai; CHEN Gang; QIN Linhao

doi:10.12382/bgxb.2025.0464

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

更新时间：2026-04-24

- Large Space Exploration and Scheme Optimization of Kill-web Design Strategy Driven by Game Confrontation
- Acta Armamentarii Vol. 47, Issue 1, Pages: 250464(2026)
- 作者机构：
  
  北京理工大学机械与车辆学院，北京 100081
  北京理工大学长三角研究院（嘉兴），浙江嘉兴 314019
- 作者简介：
- 基金信息：
- DOI：10.12382/bgxb.2025.0464
  CLC： E917
- Received：21 April 2025，
  
  Online First：11 February 2026，
  
  Published：31 January 2026
- 稿件说明：
移动端阅览
LI Chuanhao, MING Zhenjun, WANG Guoxin, et al. Large Space Exploration and Scheme Optimization of Kill-web Design Strategy Driven by Game Confrontation[J]. Acta Armamentarii, 2026, 47(1): 250464.
DOI：

LI Chuanhao, MING Zhenjun, WANG Guoxin, et al. Large Space Exploration and Scheme Optimization of Kill-web Design Strategy Driven by Game Confrontation[J]. Acta Armamentarii, 2026, 47(1): 250464. DOI： 10.12382/bgxb.2025.0464.

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。

Abstract

The existing kill-web design method based on unilateral optimization has insufficient effectiveness in game confrontation

and a bottleneck problem in the solution process is caused by the huge strategy space after the introduction of game mechanism. A large space strategy exploration and scheme optimization method for kill-web design driven by game confrontation is proposed. In order to effectively model the game confrontation of kill-web design

the strategy space and strategy constraints of kill-web game are designed based on the observation-orientation-decision-action (OODA) cycle theory

considering three types of equipment

such as reconnaissance

command and control

and strike. A matrix game model of kill-web design is established by introducing a mechanism of enemy strike actions leading to the degradation of equipment accuracy and then reducing combat effectiveness to quantify the impact of game on the revenues of both sides. Aiming at the problem that the strategy spaces of both sides in the model are 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-simulated annealing (DO-SA) algorithm is designed. The algorithm combines the strategy pool iteration mechanism of the double oracle algorithm and the global search capability of the simulated annealing algorithm

which can effectively explore the mixed strategy Nash equilibrium in the large space game and efficiently optimize the kill-web design scheme. The verified results show that the proposed method can realize the efficient solution of the optimal scheme of 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 the theoretical support and decision-making basis for the design of kill-web in the actual system confrontation.

关键词

Keywords

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