Mujoco Open Source Projects

A toolkit for developing and comparing reinforcement learning algorithms.

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

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

An elegant PyTorch deep reinforcement learning library.

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).

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

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.

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

Environment generation code for the paper "Emergent Tool Use From Multi-Agent Autocurricula"

Clean PyTorch implementations of imitation and reward learning algorithms

Real-time behaviour synthesis with MuJoCo, using Predictive Control

Deep Neuroevolution

Code for the paper "Evolution Strategies as a Scalable Alternative to Reinforcement Learning"

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

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

Soft Actor-Critic

PFRL: a PyTorch-based deep reinforcement learning library

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.

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

The Fastest Deep Reinforcement Learning Library

A collection of robotics simulation environments for reinforcement learning

Python library for Reinforcement Learning.

Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.

Unified Reinforcement Learning Framework

Code for the paper "Emergent Complexity via Multi-agent Competition"

Inverse RL algorithms (APP, MaxEnt, GAIL, VAIL)

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

A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.

A unified framework for robot learning

Tools for accelerating safe exploration research.

PyTorch implementation of Soft Actor-Critic (SAC)

Code for "Latent ODEs for Irregularly-Sampled Time Series" paper

Automatic object XML generation for Mujoco

Code for Deep RL from Human Preferences [Christiano et al]. Plus a webapp for collecting human feedback

Reaver: Modular Deep Reinforcement Learning Framework. Focused on StarCraft II. Supports Gym, Atari, and MuJoCo.

Robotic arm control in Python

Implementation of Efficient Off-policy Meta-learning via Probabilistic Context Variables (PEARL)

PyTorch implementation of deep reinforcement learning algorithms

Reinforcement learning algorithms for MuJoCo tasks

Simulate and Render MuJoCo Models in the Browser!

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

This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.

PyTorch implementation of Trust Region Policy Optimization

Minimal, clean, single-file implementations of common robotics controllers in MuJoCo.

Reinforcement Learning with Deep Energy-Based Policies

Robotics Gym Environments

An implementation of the Augmented Random Search algorithm

DrQ: Data regularized Q

Deep Planning Network: Control from pixels by latent planning with learned dynamics

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

[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering

Benchmark for Continuous Multi-Agent Robotic Control, based on OpenAI's Mujoco Gym environments.

A CLI for processing composite Wavefront OBJ files for use in MuJoCo.

Trust Region Policy Optimization with TensorFlow and OpenAI Gym

Tutorial on how to get started with MuJoCo Simulation Platform. MuJoCo stands for Multi-Joint dynamics with Contact. It was acquired and made freely available by DeepMind in October 2021, and open sourced in May 2022. Feel free to contribute. Show your support by ✨this repository.

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

A repository of high-performing hierarchical reinforcement learning models and algorithms.