An elegant PyTorch deep reinforcement learning library.

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

Massively Parallel Deep Reinforcement Learning. 🔥

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

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)

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

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.

🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

PyTorch implementation of deep reinforcement learning algorithms

Reinforcement Learning Algorithms Based on PyTorch

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022

Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]

A library for ready-made reinforcement learning agents and reusable components for neat prototyping

Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.

深度强化学习路径规划, SAC-Auto路径规划, Soft Actor-Critic算法, SAC-pytorch，激光雷达Lidar避障，激光雷达仿真模拟，Adaptive-SAC