Abstract:

As the latest development of machine learning, deep reinforcement learning has been shown in many application fields. The algorithm research and application research of deep reinforcement learning have produced many classical algorithms and typical application fields. The application of deep reinforcement learning in industrial manufacturing can realize high level control in complex environment. First of all, the research on deep reinforcement learning is summarized, and the basic principles of deep reinforcement learning are introduced, including deep learning and reinforcement learning. Then, the paper introduces the theoretical methods of the application of deep reinforcement learning algorithm. On this basis, it classifies the algorithms of deep reinforcement learning, respectively introduces the reinforcement learning algorithm based on value function and the reinforcement learning algorithm based on strategy gradient, and lists the main development results of these two kinds of algorithms, as well as other related research results. Then, the typical applications of deep reinforcement learning in industrial manufacturing are classified and analyzed. Finally, the existing problems and future development direction of deep reinforcement learning are discussed.

Key words: artificial intelligence, deep reinforcement learning, deep learning, reinforcement learning, intelligent control, intelligent manufacturing

摘要：

深度强化学习作为机器学习发展的最新成果，已经在很多应用领域崭露头角。关于深度强化学习的算法研究和应用研究，产生了很多经典的算法和典型应用领域。深度强化学习应用在智能制造中，能在复杂环境中实现高水平控制。对深度强化学习的研究进行概述，对深度强化学习基本原理进行介绍，包括深度学习和强化学习。介绍深度强化学习算法应用的理论方法，在此基础对深度强化学习的算法进行了分类介绍，分别介绍了基于值函数和基于策略梯度的强化学习算法，列举了这两类算法的主要发展成果，以及其他相关研究成果。对深度强化学习在智能制造的典型应用进行分类分析。对深度强化学习存在的问题和未来发展方向进行了讨论。

关键词: 人工智能, 深度强化学习, 深度学习, 强化学习, 智能控制, 智能制造