An elegant PyTorch deep reinforcement learning library.

Multi-Joint dynamics with Contact. A general purpose physics simulator.

Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

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).

OpenDILab Decision AI Engine

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning

C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.

A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.

Python library for Reinforcement Learning.

MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.

Real-time behaviour synthesis with MuJoCo, using Predictive Control

[CoRL '23] Dexterous piano playing with deep reinforcement learning.

Unified Reinforcement Learning Framework

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

PyTorch implementation of Soft Actor-Critic (SAC)

PyTorch implementation of Trust Region Policy Optimization

DrQ: Data regularized Q

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

A collection of robotics simulation environments for reinforcement learning