Review of deep reinforcement learning and discussions on the development of computer Go

Deep reinforcement learning which incorporates both the advantages of the perception of deep learning and the decision making of reinforcement learning is able to output control signal directly based on input images. This mechanism makes the artificial intelligence much close to human thinking modes. Deep reinforcement learning has achieved remarkable success in terms of theory and application since it is proposed. 'Chuyihao-AlphaGo', a computer Go developed by Google DeepMind, based on deep reinforcement learning, beat the world's top Go player Lee Sedol 4:1 in March 2016. This becomes a new milestone in artificial intelligence history. This paper surveys the development course of deep reinforcement learning, reviews the history of computer Go concurrently, analyzes the algorithms features, and discusses the research directions and application areas, in order to provide a valuable reference to the development of control theory and applications in a new direction.