Metadata-Version: 2.1
Name: mtrl
Version: 0.9rc1
Summary: MTRL: Multi Task RL Algorithms
Home-page: https://github.com/facbookresearch/mtrl
Author: Shagun Sodhani, Amy Zhang
Author-email: sshagunsodhani@gmail.com, amyzhang@fb.com
License: UNKNOWN
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        ![PyPI - License](https://img.shields.io/pypi/l/mtrl)
        ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mtrl)
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        [![Zulip Chat](https://img.shields.io/badge/zulip-join_chat-brightgreen.svg)](https://mtenv.zulipchat.com)
        
        # MTRL
        Multi Task RL Algorithms
        
        ## Contents
        
        1. [Introduction](#Introduction)
        
        2. [Setup](#Setup)
        
        3. [Usage](#Usage)
        
        4. [Documentation](#Documentation)
        
        5. [Contributing to MTRL](#Contributing-to-MTRL)
        
        6. [Community](#Community)
        
        7. [Acknowledgements](#Acknowledgements)
        
        ## Introduction
        
        MTRL is a library of multi-task reinforcement learning algorithms. It has two main components:
        
        * [Building blocks](https://github.com/facebookresearch/mtrl/tree/main/mtrl/agent/components) and [agents](https://github.com/facebookresearch/mtrl/tree/main/mtrl/agent) that implement the multi-task RL algorithms.
        
        * [Experiment setups](https://github.com/facebookresearch/mtrl/tree/main/mtrl/experiment) that enable training/evaluation on different setups. 
        
        Together, these two components enable use of MTRL across different environments and setups.
        
        ### List of publications & submissions using MTRL (please create a pull request to add the missing entries):
        
        * [Learning Robust State Abstractions for Hidden-Parameter Block MDPs](https://arxiv.org/abs/2007.07206)
        
        ### License
        
        * MTRL uses [MIT License](https://github.com/facebookresearch/mtrl/blob/main/LICENSE).
        
        * [Terms of Use](https://opensource.facebook.com/legal/terms)
        
        * [Privacy Policy](https://opensource.facebook.com/legal/privacy)
        
        ### Citing MTRL
        
        If you use MTRL in your research, please use the following BibTeX entry:
        ```
        @Misc{Sodhani2021MTRL,
          author =       {Shagun Sodhani and Amy Zhang},
          title =        {MTRL - Multi Task RL Algorithms},
          howpublished = {Github},
          year =         {2021},
          url =          {https://github.com/facebookresearch/mtrl}
        }
        ```
        
        ## Setup
        
        * Clone the repository: `git clone git@github.com:facebookresearch/mtrl.git`.
        
        * Install dependencies: `pip install -r requirements/dev.txt`
        
        ## Usage
        
        * MTRL supports 8 different multi-task RL algorithms as described [here]().
        
        * MTRL supports multi-task environments using [MTEnv](https://github.com/facebookresearch/mtenv). These environments include [MetaWorld](https://meta-world.github.io/) and multi-task variants of [DMControl Suite](https://github.com/deepmind/dm_control)
        
        * Refer the [tutorial]() to get started with MTRL.
        
        ## Documentation
        
        [https://mtrl.readthedocs.io](https://mtrl.readthedocs.io)
        
        ## Contributing to MTRL
        
        There are several ways to contribute to MTRL.
        
        1. Use MTRL in your research.
        
        2. Contribute a new algorithm. We currently support [8 multi-task RL algorithms]() and are looking forward to adding more environments.
        
        3. Check out the [good-first-issues](https://github.com/facebookresearch/mtenv/pulls?q=is%3Apr+is%3Aopen+label%3A%22good+first+issue%22) on GitHub and contribute to fixing those issues.
        
        4. Check out additional details [here](https://github.com/facebookresearch/mtrl/blob/main/.github/CONTRIBUTING.md).
        
        ## Community
        
        Ask questions in the chat or github issues:
        * [Chat](https://mtenv.zulipchat.com)
        * [Issues](https://https://github.com/facebookresearch/mtrl/issues)
        
        ## Acknowledgements
        
        * Project file pre-commit, mypy config, towncrier config, circleci etc are based on same files from [Hydra](https://github.com/facebookresearch/hydra).
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
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