In recent years, with the continuous development of reinforcement learning (RL), we have seen promising results in processing continuous action RL tasks 1,2,3,4,5. In dealing with some continuous ...

Reinforcement learning offers efficient solutions for optimizing complex decision-making tasks through continuous state-action-reward cycle with real-time adaptability. This work presents twin delayed ...