计算机科学与探索2024，Vol.18Issue(6)：1457-1475,19.DOI:10.3778/j.issn.1673-9418.2312006
强化学习中的注意力机制研究综述
Review of Attention Mechanisms in Reinforcement Learning
摘要
Abstract
In recent years,the combination of reinforcement learning and attention mechanisms has attracted an increasing attention in algorithmic research field.Attention mechanisms play an important role in improving the performance of algorithms in reinforcement learning.This paper mainly focuses on the development of attention mechanisms in deep reinforcement learning and examining their applications in the multi-agent reinforcement learning domain.Relevant researches are conducted accordingly.Firstly,the background and development of attention mechanisms and reinforcement learning are introduced,and relevant experimental platforms in this field are also presented.Secondly,classical algorithms of reinforcement learning and attention mechanisms are reviewed and attention mechanism is categorized from different perspectives.Thirdly,practical applications of attention mechanisms in the reinforcement field are sorted out based on three types of tasks including fully cooperative,fully competitive and mixed,with focus on the application in the field of multi-agent.Finally,the improvement of attention mechanisms on reinforcement learning algorithms is summarized.The challenges and future prospects in this field are discussed.关键词
强化学习/注意力机制/多智能体系统Key words
reinforcement learning/attention mechanism/multi-agent system分类
信息技术与安全科学引用本文复制引用
夏庆锋,许可儿,李明阳,胡凯,宋利鹏,宋志强,孙宁..强化学习中的注意力机制研究综述[J].计算机科学与探索,2024,18(6):1457-1475,19.基金项目
辽宁省科技厅机器人学国家重点实验室联合开放基金(2021-KF-22-19).This work was supported by the Joint Fund of Science&Technology Department of Liaoning Province and State Key Laboratory of Robotics(2021-KF-22-19). （2021-KF-22-19）
