论文:2022,Vol:40,Issue(4):755-763
引用本文:
魏娜, 刘明雍. 基于贝叶斯纳什均衡的不完全信息博弈目标分配决策[J]. 西北工业大学学报
WEI Na, LIU Mingyong. Target allocation decision of incomplete information game based on Bayesian Nash equilibrium[J]. Northwestern polytechnical university

基于贝叶斯纳什均衡的不完全信息博弈目标分配决策
魏娜1,2, 刘明雍1
1. 西北工业大学 航海学院, 陕西 西安 710072;
2. 西安石油大学 电子工程学院, 陕西 西安 710065
摘要:
针对AUV(autonomous underwater vehicle)协同对抗过程中的信息不完全问题,用不完全信息博弈理论研究AUV的对抗行为。以对抗双方的剩余生存概率和武器消耗量为评价指标,加入位置误差影响因子,建立了面向不完全信息的AUV博弈对抗目标分配模型。以贝叶斯纳什均衡理论为基础,通过虚拟参与者"自然(Nature)",预先设置关于攻防策略类型的先验概率,选择出待分配的AUV类型,然后通过后验概率不断修正关于对方采用的目标分配策略类型的判断。提出了基于多目标离散粒子群的不完全信息目标分配求解算法,得到了博弈对抗双方的贝叶斯纳什均衡目标分配策略,为指挥官的作战指挥提供了策略选择帮助。
关键词:    目标分配    不完全信息博弈    贝叶斯纳什均衡    离散粒子群算法   
Target allocation decision of incomplete information game based on Bayesian Nash equilibrium
WEI Na1,2, LIU Mingyong1
1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Electronic Engineering, Xi'an Shiyou University, Xi'an 710065, China
Abstract:
Aiming at the incomplete information of AUV cooperative confrontation, the incomplete information game theory is used to study the confrontation behavior of AUVs. Taking the remaining survival probability and weapon consumption as the evaluation indicators, adding the position error factor, an AUV game confrontation target allocation model for incomplete information is established. In terms of the Bayesian Nash equilibrium theory, the prior probabilities of the offensive and defensive strategy types are set by the virtual participant "Nature" in advance. Then the types of AUVs to be allocated are selected, and the judgment on the types of the target assignment strategies adopted by the other party are modified through the posterior probability. An algorithm for solving incomplete information target assignment based on the multi-target discrete particle swarms is proposed, and the Bayesian Nash equilibrium target assignment strategies of the two sides are obtained, which provides strategic choice help for the commander's combat command.
Key words:    target allocation    incomplete information game    Bayesian Nash equilibrium    discrete particle swarm optimization   
收稿日期: 2021-10-09     修回日期:
DOI: 10.1051/jnwpu/20224040755
基金项目: 国家自然科学基金面上项目(51679201,51879219)资助
通讯作者: 刘明雍(1971-),西北工业大学教授,主要从事惯性导航与组合导航理论与应用、水下武器系统研究。e-mail:liumingyong@nwpu.edu.cn     Email:liumingyong@nwpu.edu.cn
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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