记笔记

Apollonius Partitions Based Pursuit-evasion Game Strategies by Q-Learning Approach

Qing Wang¹KaiQi Wu²JianFeng Ye³YongBao Wu³Lei Xue³

1. SEU-Monash Joint Graduate school,Southeast University 2. The College of Software Engineering,Southeast University 3. School of Automation,Southeast University,Key Laboratory of Measurement and Control of Complex Systems of Engineering,Ministry of Education

摘要：This paper studies a classical single pursuer and single evader pursuit-evasion game.The pursuer attempts to capture the slower evader who aims to extend its lifetime during the game.To simplify this question,requiring the evader to take fixation strategy which is choosing the farthest point in its current dominant region as aimpoint and moving at a constant speed.Assuming the pursuer is faster than the evader.Then,the speed ratio is a constant.The instaneous state space will be partitioned into pursuer’s dominant zone and evader’s dominant zone by the generalized Apollonius circle.The pursuit strategy is based on minimizing the area of the evader’s dominant region.Furthermore,we propose a supermodular game for this game.Thus,the existence of the Nash equilibrium is guaranteed.Simulation results based on Q-learning are presented to solve the problem,which shows the effectiveness of this method.

关键词：

Pursuit-evasion game; Nash equilibrium; Q-learning;

基金：

supported in part by the National Natural S cience Foundation of China under grants 62073225； the Natural Science Foundation of Jiangsu Province of China under grants BK20202006； the Fundamental Research Funds for the Central Universities； the"Zhishan"Scholars Programs of Southeast University；

会议名称：

第41届中国控制会议

会议时间：

2022-07-25

会议地点：

中国安徽合肥