There are 5 repositories under actor-critic topic.
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
Minimal and Clean Reinforcement Learning Examples
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Deep Reinforcement Learning with pytorch & visdom
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
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)
Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog
Simple A3C implementation with pytorch + multiprocessing
A3C LSTM Atari with Pytorch plus A3G design
PyTorch C++ Reinforcement Learning
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Implementations of Reinforcement Learning Models in Tensorflow
PyTorch implementation of Soft Actor-Critic (SAC)
DrQ: Data regularized Q
🔥🌟《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!
[파이썬과 케라스로 배우는 강화학습] 예제
Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch
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
PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments
Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)
Reinforcement learning framework to accelerate research
Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games
"Neural Combinatorial Optimization with Reinforcement Learning"[Bello+, 2016], Traveling Salesman Problem solver