Metadata-Version: 2.1
Name: modular-mujoco-envs
Version: 1.2
Summary: Modular MuJoCo Environments
Home-page: https://github.com/brandontrabucco/modular-mujoco-envs
Author: Brandon Trabucco
Author-email: brandon@btrabucco.com
License: MIT
Download-URL: https://github.com/brandontrabucco/modular-mujoco-envs/archive/v1_2.tar.gz
Keywords: Deep Learning,Deep Reinforcement Learning
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
License-File: LICENSE

# Modular MuJoCo Environments

Collection of modular MuJoCo environments for benchmarking morphology agnostic reinforcement learning algorithms. The contained environments are primarily based on the paper "One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control" by Wenlong Huang, Igor Mordatch, and Deepak Pathak, from ICML 2020.

## Installation

```bash
pip install modular-mujoco-envs
```

