Pursuit-evasion games are ubiquitous in nature and in an artificial world. In nature, pursuer(s) and evader(s) are intelligent agents that can learn from experience, and dynamics (i.e., Newtonian or Lagrangian) is vital for the pursuer and the evader in some scenarios. To this end, this paper addresses the pursuit-evasion game of intelligent agents from the perspective of dynamics. A bio-inspired dynamics formulation of a pursuit-evasion game and baseline pursuit and evasion strategies are introduced at first. Then, reinforcement learning techniques are used to mimic the ability of intelligent agents to learn from experience. Based on the dynamics formulation and reinforcement learning techniques, the effects of improving both pursuit and evasion strategies based on experience on pursuit-evasion games are investigated at two levels 1) individual runs and 2) ranges of the parameters of pursuit-evasion games. Results of the investigation are consistent with nature observations and the natural law - survival of the fittest. More importantly, with respect to the result of a pursuit-evasion game of agents with baseline strategies, this study achieves a different result. It is shown that, in a pursuit-evasion game with a dynamics formulation, an evader is not able to escape from a slightly faster pursuer with an effective learned pursuit strategy, based on agile maneuvers and an effective learned evasion strategy.
Cooperative Nonlinear Guidance Strategies for Guaranteed Pursuit-Evasion
Intelligent Systems and Control Lab, Department of Aerospace Engineering, Indian Institute of Technology Bombay（智能系统与控制实验室，航空航天工程系，印度理工学院班加罗尔）；GALACxIS Lab, Department of Aerospace Engineering and Engineering Mechanics, University of Cincinnati（GALACxIS实验室，航空航天工程与工程力学系，辛辛那提大学）
Control Strategies for Pursuit-Evasion Under Occlusion Using Visibility and Safety Barrier Functions
University of California San Diego（加利福尼亚大学圣迭戈分校）；General Dynamics Mission Systems（通用动力任务系统公司）；Honda R&D Co. Ltd.（本田研发有限公司）；University of Michigan（密歇根大学）
Value of Multi-pursuer Single-evader Pursuit-evasion Game with Terminal Cost of Evader's Position: Relaxation of Convexity Condition
School of Mathematics and Statistics, Beijing Institute of Technology（北京理工大学数学与统计学院）；National Key Lab of Autonomous Intelligent Unmanned Systems（自主智能无人系统全国重点实验室）；College of Information Science and Technology, Beijing University of Chemical Technology（北京化工大学信息科学与技术学院）；School of Automation, Beijing Institute of Technology（北京理工大学自动化学院）；Beijing Institute of Technology Chongqing Innovation Center（北京理工大学重庆创新中心）
