Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
-
Updated
Jun 3, 2024 - Python
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Real-time behaviour synthesis with MuJoCo, using Predictive Control
A collection of robotics simulation environments for reinforcement learning
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
Simple kinematics calculation toolkit for robotics
Gym environments for NeuroMechFly in various physics simulators
A model predictive controller for quadruped robots based on the single rigid body model and written in python. Gradient-based (acados) or Sampling-based (jax).
OpenDILab Decision AI Engine
A Fast, Portable Deep Reinforcement Learning Library for Continuous Control
MuJoCo fruit fly body model and reinforcement learning tasks
Reinforcement learning environments for planar robotics based on MuJoCo
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
The Simple Simulator: Simulation Made Simple
Python library for Reinforcement Learning.
Unified Reinforcement Learning Framework
An elegant PyTorch deep reinforcement learning library.
Add a description, image, and links to the mujoco topic page so that developers can more easily learn about it.
To associate your repository with the mujoco topic, visit your repo's landing page and select "manage topics."