群体追逃微分博弈
Group pursuit-evasion differential games
高红伟 1孟斌斌 2刘剑 3戴照鹏1
作者信息
- 1. 青岛大学数学与统计学院,山东青岛 266071
- 2. 军事科学院国防科技创新研究院智能博弈与决策实验室,北京 100071
- 3. 海军潜艇学院,山东青岛 266199
- 折叠
摘要
本文以微分博弈和经典的追逃问题为主线,对群体追逃微分博弈的历史发展脉络进行梳理.针对大规模群体追逃问题,从平均场博弈视角出发,阐释了强化学习技术的应用前景.提出探索解决逆向追逃微分博弈的观点,可适用于水下无人舰艇、陆地机器人以及空中无人机集群等同类场景.区别于其他综述性文章,作者对于俄罗斯以及苏联在本领域发展历史中代表性的学术流派给予了较多关注.
Abstract
With differential games and classical pursuit-evasion problems as the main focus,this article aims to trace the historical development of group pursuit-evasion differential games.By addressing large-scale group pursuit-evasion issues from the point of mean-field games,the prospects of applying reinforcement learning techniques are elucidated.It proposes exploring solutions to inverse pursuit-evasion differential games,suitable for scenarios such as underwater autonomous vessels,terrestrial robots,and swarms of unmanned aerial vehicles.Diverging from other review papers,it devotes significant attention to the distinctive academic schools of thought in Russia and the former Soviet Union,highlighting their influence in the evolution of this field.
关键词
追逃微分博弈/群体智能博弈/平均场博弈/逆向博弈/强化学习Key words
pursuit-evasion differential games/swarm intelligence games/mean-field games/inverse game theory/reinforcement learning引用本文复制引用
出版年
2024
NETL
NSTL
万方数据