Chinese Journal of Intelligent Science and Technology ›› 2020, Vol. 2 ›› Issue (4): 314-326.doi: 10.11959/j.issn.2096-6652.202034

• Special Issue: Deep Reinforcement Learning • Previous Articles     Next Articles

An overview on algorithms and applications of deep reinforcement learning

Zhaoyang LIU1, Chaoxu MU1, Changyin SUN2   

  1. 1 School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
    2 School of Automation, Southeast University, Nanjing 210096, China
  • Revised:2020-12-03 Online:2020-12-15 Published:2020-12-01
  • Supported by:
    The National Natural Science Foundation of China(61773284)


Deep reinforcement learning (DRL) is mainly applied to solve the perception-decision problem, and has become an important research branch in the field of artificial intelligence.Two kinds of DRL algorithms based on value function and policy gradient were summarized, including deep Q network, policy gradient as well as related developed algorithms.In addition, the applications of DRL in video games, navigation, multi-agent cooperation and recommendation field were intensively reviewed.Finally, a prospect for the future research of DRL was made, and some research suggestions were given.

Key words: artificial intelligence, deep reinforcement learning, value function, policy gradient, navigation, cooperation, complex environment, generalization, robustness

CLC Number: 

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