强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

An elegant PyTorch deep reinforcement learning library.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

Repo for the Deep Reinforcement Learning Nanodegree program

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Massively Parallel Deep Reinforcement Learning. 🔥

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).

Modularized Implementation of Deep RL Algorithms in PyTorch

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

For trading. Please star.

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

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)

This is the official implementation of Multi-Agent PPO (MAPPO).

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch