基于博弈理论的有人/无人平台协同任务决策  

Collaborative Task Decision of Manned/Unmanned Platforms Based on Game Theory

作　　者：刘朝辉 任康瑞 翁世倩 李兵飞 LIU Zhao-hui;REN Kang-rui;WENG Shi-Qian;LI Bing-fei(National Key Laboratory of Science and Technology on Avionics System Integration,Shanghai 200241,China;School of Electronic and Information Engineering,Tongji University,Shanghai 201804,China;Unit 93184,Beijing 100071,China;China National Aeronautical Radio Electronic Research Institute,Shanghai 200241,China)

机构地区：[1]航空电子系统综合技术重点实验室,上海200241 [2]同济大学电子与信息工程学院,上海201804 [3]93184部队,北京100071 [4]中国航空无线电电子研究所,上海200241

出　　处：《计算机仿真》2024年第11期1-5,共5页Computer Simulation

摘　　要：通过对想定任务场景建模,分析传感器探测、毁伤、干扰等概率信息不确定性,提出不确定性信息下有人/无人平台协同任务博弈决策求解方法。以红蓝双方传感器探测概率、信息干扰概率、武器毁伤概率信息为依据,构建协同任务博弈决策模型。结合区间数排序方法和量子粒子群算法,解算不确定性信息下有人/无人平台协同任务博弈问题的纳什均衡解。仿真研究表明,量子粒子群算法在应用场景和约束条件下,求解纳什均衡问题具有可行性和高效性,为复杂环境下协同任务博弈决策问题求解提供了解决思路。By modeling the scenario of a hypothetical task and analyzing the uncertainty of probability information such as sensor detection,damage,and interference,a game decision-solving method for manned/unmanned platform collaborative tasks under uncertainty information is proposed.Based on the detection probability,information interference probability and weapon damage probability information of red and blue sensors,a cooperative task game Decision model is constructed.Combining the interval number sorting method and the quantum particle swarm optimization algorithm,the Nash equilibrium solution of the game problem of manned/unmanned platform collaborative task under uncertainty information is solved.Simulation studies have shown that the quantum particle swarm optimization algo-rithm is feasible and efficient in solving Nash equilibrium problems under the scenarios and constraints in this paper,providing a solution for collaborative task game decision-making problems in complex environments.

关 键 词：不确定性信息 有人/无人平台协同 博弈决策 量子粒子群 区间数排序 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]