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)

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

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

Massively Parallel Deep Reinforcement Learning. 🔥

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)

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

Confetti! Who doesn't like confetti?

SRCL is an open-source React component and style repository that helps you build web applications, desktop applications, and static websites with terminal aesthetics.

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

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

High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..

Soft Actor-Critic

Reference BLEU implementation that auto-downloads test sets and reports a version string to facilitate cross-lab comparisons

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.

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🐋 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)

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

RLGF is a general training framework suitable for UAV deep reinforcement learning tasks. And integrates multiple mainstream deep reinforcement learning algorithms(SAC, DQN, DDQN, PPO, Dueling DQN, DDPG).

s(hortcut)-ack: a faster way to use ag, ack (or grep)!

Python port of Moses tokenizer, truecaser and normalizer

PyTorch implementation of deep reinforcement learning algorithms

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