多智能体强化学习算法研究综述OA北大核心CSTPCD

In recent years,the technique of multi-agent reinforcement learning algorithm has been widely used in the field of artificial intelligence.This paper systematically analyses the multi-agent reinforcement learning algo-rithm,examines its application and progress in multi-agent systems,and explores the relevant research results in depth.Firstly,it introduces the research background and development history of multi-agent reinforcement learning and summarizes the existing relevant research results.Secondly,it briefly reviews the application of traditional rein-forcement learning algorithms under different tasks.Then,it highlights the classification of multi-agent reinforce-ment learning algorithms and their application in multi-agent systems according to the three main types of tasks(path planning,pursuit and escape game,task allocation),challenges,and solutions.Finally,it explores the existing algorithm training environments in the field of multi-agents,summarizes the improvement of deep learning on multi-agent reinforcement learning algorithms,proposes challenges and looks forward to future research directions in this field.