Recently, the deep reinforcement learning method based on actor-critic has a competent performance in continuous action control tasks, such as the proposed deep deterministic policy gradient (DDPG) ...

Deep Deterministic Policy Gradient (DDPG) This repository contains a clean and minimal implementation of Deep Deterministic Policy Gradient (DDPG) algorithm in Pytorch. DDPG is a model-free RL ...

This paper proposes a multi-timescale method based on the DQN-DDPG algorithms for optimal voltage control in a DN. The DQN algorithm and the DDPG algorithm were used to train the dynamic responses of ...

DDPG is derived from two algorithms Deep-Q-Network (DQN) and Deterministic Policy Gradients (DPG). DPG is an efficient gradient computation for deterministic policies. DQN has few features such as ...

Then, this paper uses the designed switcher to automatically switch between DDPG and MPC algorithms according to the constraints that the current robot needs to meet to realize local path planning.