关键词: 分层强化学习, 多智能体系统, 维数灾难

Abstract: Reinforcement learning is an approach that an agent can learn its behaviors through trial-and-error interaction with a dynamic environment.It has been an important branch of machine learning for its self-learning and online learning capabilities. But reinforcement learning is bedeviled by the curse of dimensionality.Recently，Hierarchical Reinforcement Learning（HRL） has made great progresses to combat the curse of dimensionality.And the HRL approaches have been being applied to multi-agent system.The recent advances in HRL are surveyed in this paper.Then，some open problems are discussed.Finally，the HRL prospects are shown.

Key words: Hierarchical Reinforcement Learning, multi-agent system, curse of dimensionality