基于协同对抗的水下博弈策略优化 -- 西北工业大学学报,2019,37(1):63-69
论文:2019,Vol:37,Issue(1):63-69
引用本文:
魏娜, 刘明雍, 张帅, 张小件. 基于协同对抗的水下博弈策略优化[J]. 西北工业大学学报
WEI Na, LIU Mingyong, ZHANG Shuai, ZHANG Xiaojian. Optimizing Underwater Game Strategy Based on Cooperative Confrontation[J]. Northwestern polytechnical university

基于协同对抗的水下博弈策略优化
魏娜1,2, 刘明雍1, 张帅1, 张小件1
1. 西北工业大学 航海学院, 陕西 西安 710072;
2. 西安石油大学 陕西省油气井测控技术重点实验室, 陕西 西安 710065
摘要:
针对多自主水下航行器(autonomous underwater vehicle,AUV)的水下协同对抗博弈问题,以博弈论为基础,多AUV的多次对抗为作战背景,从同时考虑敌我双方对抗策略的角度出发,对多AUV的动态协同攻防对抗策略问题进行了研究。考虑生存概率指标函数和水下环境影响,建立了基于动态博弈的多自主水下航行器的单元目标分配模型,构建博弈矩阵。在此基础上,采用粒子群算法,通过求解博弈模型的纳什均衡解,形成博弈对抗双方的最优攻防决策方案,并对所研究的攻防策略优化方法进行了仿真验证,结果表明该模型和方法的可行性和有效性。
关键词:    协同对抗    自主水下航行器    目标分配    动态博弈模型    纳什均衡    粒子群算法   
Optimizing Underwater Game Strategy Based on Cooperative Confrontation
WEI Na1,2, LIU Mingyong1, ZHANG Shuai1, ZHANG Xiaojian1
1. School of Marine Engineering, Northwestern Polytechnical University, Xi'an 710072, China;
2. Shaanxi Key Laboratory of Measurement and Control Technology for Oil and Gas Well, Xi'an Shiyou University, Xi'an 710065, China
Abstract:
Based on the multi-round confrontation of multiple Autonomous Underwater Vehicles (AUVS), the concept of Nash equilibrium is used to solve the problem of underwater dynamic cooperative confrontation of multiple AUVs. From the perspective of confrontation strategies of both sides of an AUV and considering the influence of survival probability index function and the uncertain factors of underwater environment, the unit target allocation model of multiple AUVs based on dynamic game and game matrix are established. By solving the Nash equilibrium solution of the game model, the particle swarm optimization algorithm is applied to solve the Nash equilibrium point for obtaining the optimal attack and defense strategies of both sides. The feasibility and effectiveness of the method was verified by simulation.
Key words:    cooperative confrontation    autonomous underwater vehicles    target allocation    dynamic game model    Nash equilibrium    particle swarm optimization   
收稿日期: 2018-03-01     修回日期:
DOI: 10.1051/jnwpu/20193710063
基金项目: 国家自然科学基金(51679201,51879219)与陕西省教育厅科研计划重点项目(18JS094)资助
通讯作者:     Email:
作者简介: 魏娜(1980-),女,西北工业大学博士研究生,主要从事自主水下航行器与自主移动机器人协同控制与决策研究。
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