Chinese Journal of Intelligent Science and Technology ›› 2020, Vol. 2 ›› Issue (2): 101-106.doi: 10.11959/j.issn.2096-6652.202011

• Review Intelligence •     Next Articles

Reinforcement learning:toward action-knowledge merged intelligent mechanisms and algorithms

Fei-Yue WANG1,2,3,Dongpu CAO4,Qinglai WEI1,2,3   

  1. 1 The State Key Laboratory for Management and Control of Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China
    2 University of Chinese Academy of Sciences,Beijing 100049,China
    3 Qingdao Academy of Intelligent Industries,Qingdao 266109,China
    4 University of Waterloo,Waterloo N2L 3G1,Canada
  • Revised:2020-05-20 Online:2020-06-20 Published:2020-07-14


This article discusses briefly the history,the state of the art and the future of reinforcement learning,and outlines a roadmap of evolution from learning by doing,doing with planning to parallel intelligence that combining learning virtually in artificial systems and acting accordingly in actual systems.

Key words: reinforcement learning, dynamic programming, deep learning, parallel learning, artificial intelligence

CLC Number: 

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