There are 8 repositories under ddpg topic.
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
强化学习中文教程(蘑菇书🍄),在线阅读地址:https://datawhalechina.github.io/easy-rl/
Repo for the Deep Reinforcement Learning Nanodegree program
Massively Parallel Deep Reinforcement Learning. 🔥
Modularized Implementation of Deep RL Algorithms in PyTorch
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
For trading. Please star.
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
Python library for Reinforcement Learning.
This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)
A PyTorch library for building deep reinforcement learning agents.
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch
Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
PyTorch implementation of deep reinforcement learning algorithms
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.
🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!
lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
Build environment and train a robot arm from scratch (Reinforcement Learning)
An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
Simulated the scenario between edge servers and users with a clear graphic interface. Also, implemented the continuous control with Deep Deterministic Policy Gradient (DDPG) to determine the resources allocation (offload targets, computational resources, migration bandwidth) in the edge servers
Implementation of algorithms for continuous control (DDPG and NAF).
A library for ready-made reinforcement learning agents and reusable components for neat prototyping
Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]
Pytorch Implementation of Reinforcement Learning Algorithms ( Soft Actor Critic(SAC)/ DDPG / TD3 /DQN / A2C/ PPO / TRPO)
End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo
Solving OpenAI Gym problems.
Implementation of the algorithm in Python 3, TensorFlow and OpenAI Gym