摘要： 研究了优先扫描的强化学习方法,通过定义新的迹,把多步截断即时差分学习用于集成规划的优先扫描强化学习,用多步截断即时差分来定义扫描优先权,提出一种改进的优先扫描强化学习算法并进行仿真实验,实验结果表明,新算法的学习效率有明显的提高。

关键词: 强化学习, 优先扫描, 多步截断, Markov过程

Abstract: Prioritized sweeping reinforcement learning method is investigated. Giving a new definition of eligibility traces, truncated multi-step temporal difference learning can be used in integrating planning prioritized sweeping learning. Setting the priority as truncated multi-step temporal errors, an advanced prioritized sweeping RL algorithm is proposed. The results of experiment show that the algorithm has more effective performance.

中图分类号: 

• TP181