_ __ _ __ __ _ __
_____ _____ (_)/ /__ (_)/ /_ ____/ /___ _____ (_)____/ /___
/ ___// ___// // //_// // __/______ / __ // _ \ / ___// // __ // _ \
(__ )/ /__ / // ,< / // /_ /_____// /_/ // __// /__ / // /_/ // __/
/____/ \___//_//_/|_|/_/ \__/ \__,_/ \___/ \___//_/ \__,_/ \___/
<br>
<p align="center">
<a href="https://github.com/airbus/scikit-decide/actions/workflows/ci.yml?query=branch%3Amaster">
<img src="https://img.shields.io/github/actions/workflow/status/airbus/scikit-decide/ci.yml?branch=master&logo=github&label=CI%20status" alt="actions status">
</a>
<a href="https://github.com/airbus/scikit-decide/tags">
<img src="https://img.shields.io/github/tag/airbus/scikit-decide.svg?label=current%20version" alt="version">
</a>
<a href="https://github.com/airbus/scikit-decide/stargazers">
<img src="https://img.shields.io/github/stars/airbus/scikit-decide.svg" alt="stars">
</a>
<a href="https://github.com/airbus/scikit-decide/network">
<img src="https://img.shields.io/github/forks/airbus/scikit-decide.svg" alt="forks">
</a>
</p>
<br>
# Scikit-decide for Python
Scikit-decide is an AI framework for Reinforcement Learning, Automated Planning and Scheduling.
This framework was initiated at [Airbus](https://www.airbus.com) AI Research and notably received contributions through the [ANITI](https://aniti.univ-toulouse.fr/en/) and [TUPLES](https://tuples.ai/) projects, and also from [ANU](https://www.anu.edu.au/).
## Installation
Quick version:
```shell
pip install scikit-decide[all]
```
For more details, see the [online documentation](https://airbus.github.io/scikit-decide/install).
## Documentation
The latest documentation is available [online](https://airbus.github.io/scikit-decide).
## Examples
Some educational notebooks are available in `notebooks/` folder.
Links to launch them online with [binder](https://mybinder.org/) are provided in the
[Notebooks section](https://airbus.github.io/scikit-decide/notebooks) of the online documentation.
More examples can be found as Python scripts in the `examples/` folder, showing how to import or define a domain,
and how to run or solve it. Most of the examples rely on scikit-decide Hub, an extensible catalog of domains/solvers.
## Contributing
See more about how to contribute in the [online documentation](https://airbus.github.io/scikit-decide/contribute).
Raw data
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