The deep reinforcement learning value has received a lot of attention from researchers since it was proposed. It combines the data representation capability of deep learning and the self-learning capability of reinforcement learning to give agents the ability to make direct action decisions on raw data. Deep reinforcement learning continuously optimizes the control strategy by using value function approximation and strategy search methods, ultimately resulting in an agent with a higher level of understanding of the target task. This paper provides a systematic description and summary of the co...
