计算机应用与软件2024，Vol.41Issue(4)：1-15,15.DOI:10.3969/j.issn.1000-386x.2024.04.001
竞争与合作视角下的多Agent强化学习研究进展
RECENT PROCESS AND PROSPECT OF MULTI-AGENT REINFORCEMENT LEARNING UNDER THE PERSPECTIVE OF COMPETITION AND COOPERATION
摘要
Abstract
With the rapid development of deep learning and reinforcement learning,multi-agent reinforcement learning(MARL)has become a common approach to solve the large scale complex sequential decision-making problem.In order to promote the development of this field,this paper collects and reviews recent research results from the perspective of competition and cooperation.This paper introduced deep reinforcement learning and introduced the basic theoretical framework of MARL-Markov game and extensive game,and especially emphasized the reinforcement learning algorithms developed recently in three scenarios of competition,cooperation and mixture.This paper discussed the core challenge of MARL that was non-stationary of the environment,and an example was given to summarize and prospect its solutions.关键词
深度学习/强化学习/多Agent强化学习/环境的不稳定性Key words
Deep learning/Reinforcement learning/Multi-agent reinforcement learning/Non-stationary of the environment分类
信息技术与安全科学引用本文复制引用
田小禾,李伟,许铮,刘天星,戚骁亚,甘中学..竞争与合作视角下的多Agent强化学习研究进展[J].计算机应用与软件,2024,41(4):1-15,15.基金项目
广东省季华实验室基金项目(X190021TB190) （X190021TB190）
上海市科学技术委员会项目(1951113200). （1951113200）
