Volume 37, Number 1, February 2019
|Page(s)||63 - 69|
|Published online||03 April 2019|
Optimizing Underwater Game Strategy Based on Cooperative Confrontation
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
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.
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。
Key words: cooperative confrontation / autonomous underwater vehicles / target allocation / dynamic game model / Nash equilibrium / particle swarm optimization
关键字 : 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
© 2019 Journal of Northwestern Polytechnical University
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