sac

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".

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.

Python library for Reinforcement Learning.

JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.

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 Soft Actor-Critic (SAC)

PyTorch implementation of deep reinforcement learning algorithms

Reinforcement Learning Algorithms Based on PyTorch

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

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

DrQ: Data regularized Q

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