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Python mujoco-py Libraries

Simple renderer for use with MuJoCo (>=2.1.2) Python Bindings.
Simple renderer for use with MuJoCo (=2.1.2) Python Bindings.

Viewer for MuJoCo in Python Interactive renderer to use with the official Python bindings for MuJoCo. Starting with version 2.1.2, MuJoCo comes with n

Rohan P. Singh 62 Dec 30, 2022
PyTorch implementation of the ExORL: Exploratory Data for Offline Reinforcement Learning

ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg

Denis Yarats 52 Jan 1, 2023
Tianshou - An elegant PyTorch deep reinforcement learning library.
Tianshou - An elegant PyTorch deep reinforcement learning library.

Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on

Tsinghua Machine Learning Group 5.5k Jan 5, 2023
DM-ACME compatible implementation of the Arm26 environment from Mujoco
DM-ACME compatible implementation of the Arm26 environment from Mujoco

ACME-compatible implementation of Arm26 from Mujoco This repository contains a customized implementation of Mujoco's Arm26 model, that can be used wit

null 1 Dec 24, 2021
Training code and evaluation benchmarks for the
Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.

Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur

Nicklas Hansen 101 Nov 1, 2022
Gym environments used in the paper:
Gym environments used in the paper: "Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors"

gym_multirotor Gym to train reinforcement learning agents on UAV platforms Quadrotor Tiltrotor Requirements This package has been tested on Ubuntu 18.

Aditya M. Deshpande 19 Dec 29, 2022
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).
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).

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).

Ilya Kostrikov 3k Dec 31, 2022
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

dm_control: DeepMind Infrastructure for Physics-Based Simulation. DeepMind's software stack for physics-based simulation and Reinforcement Learning en

DeepMind 3k Dec 31, 2022
Multi-Joint dynamics with Contact. A general purpose physics simulator.

MuJoCo Physics MuJoCo stands for Multi-Joint dynamics with Contact. It is a general purpose physics engine that aims to facilitate research and develo

DeepMind 5.2k Jan 2, 2023
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).
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).

pytorch-a2c-ppo-acktr Update (April 12th, 2021) PPO is great, but Soft Actor Critic can be better for many continuous control tasks. Please check out

Ilya Kostrikov 3k Jan 9, 2023
PyTorch implementation of Trust Region Policy Optimization

PyTorch implementation of TRPO Try my implementation of PPO (aka newer better variant of TRPO), unless you need to you TRPO for some specific reasons.

Ilya Kostrikov 366 Nov 15, 2022
Implement A3C for Mujoco gym envs
Implement A3C for Mujoco gym envs

pytorch-a3c-mujoco Disclaimer: my implementation right now is unstable (you ca refer to the learning curve below), I'm not sure if it's my problems. A

Andrew 70 Dec 12, 2022
Proto-RL: Reinforcement Learning with Prototypical Representations

Proto-RL: Reinforcement Learning with Prototypical Representations This is a PyTorch implementation of Proto-RL from Reinforcement Learning with Proto

Denis Yarats 74 Dec 6, 2022
Model-based reinforcement learning in TensorFlow

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

null 46 Nov 9, 2022
An open source robotics benchmark for meta- and multi-task reinforcement learning

Meta-World Meta-World is an open-source simulated benchmark for meta-reinforcement learning and multi-task learning consisting of 50 distinct robotic

Reinforcement Learning Working Group 823 Jan 6, 2023
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

Coach Coach is a python reinforcement learning framework containing implementation of many state-of-the-art algorithms. It exposes a set of easy-to-us

Intel Labs 2.2k Jan 5, 2023