Duality in Deep Reinforcement Learning— Implementation

More and more deep reinforcement learning algorithms have been proposed and demonstrated on a series of decision-making domains. With duality in deep reinforcement learning substantially summarized, this paper summarizes duality in deep reinforcement learning and proposes the duality with priority in Part I-Theory. It proposed an asynchronous architecture for dual priority in deep reinforcement learning. Experiments improve the state of the art on discrete action environments as well as continuous control tasks, while demonstrate its final performance and data efficiency.