rl4aa24-tutorial

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rl4aa24-tutorial

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Hands-on tutorial about Meta RL and GP-MPC at the RL4AA'24 workshop.

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[![DOI](https://zenodo.org/badge/700362904.svg)](https://zenodo.org/doi/10.5281/zenodo.10886639)
[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

# Tutorial on Meta-Reinforcement Learning and GP-MPC at the RL4AA'24 Workshop

This repository contains the material for the second day of the [RL4AA'24](https://indico.scc.kit.edu/event/3746/timetable/#all.detailed) event.

Homepage for RL4AA Collaboration: [https://rl4aa.github.io/](https://rl4aa.github.io/)

## Theory slides for the tutorial

- [Concepts to overcome challenges in applying RL to accelerators](https://indico.scc.kit.edu/event/3746/sessions/3777/), Simon Hirländer

## Python tutorial: meta reinforcement learning implementation example

- GitHub repository containing the material: [https://github.com/RL4AA/RL4AA24](https://github.com/RL4AA/rl4aa24-tutorial/)
- Tutorial in slide form: [here](https://rl4aa.github.io/rl4aa24-tutorial/)

## Getting started

- First, download the material to your local disk by cloning the repository:
`git clone https://github.com/RL4AA/rl4aa24-tutorial.git`
- If you don't have git installed, you can click on the green button that says "Code", and choose to download it as a `.zip` file.

### Part 1 Meta-RL

The material is located in the `meta-rl` folder.

```bash
cd meta-rl
```

### Part 2 Model-based RL

The material is located in the `gp-mpc` folder.

```bash
cd gp-mpc
```

## Citing the tutorial

This tutorial is uploaded to [Zenodo](https://zenodo.org/doi/10.5281/zenodo.10886639).
Please use the following DOI when citing this code:

```bibtex
@software{hirlaender_2024_10887397,
    title        = {{Tutorial on Meta-Reinforcement Learning and GP-MPC at the RL4AA'24 Workshop}},
    author       = {Hirlaender, Simon and Kaiser, Jan and Xu, Chenran and Santamaria Garcia, Andrea},
    year         = 2024,
    month        = mar,
    publisher    = {Zenodo},
    doi          = {10.5281/zenodo.10887397},
    url          = {https://doi.org/10.5281/zenodo.10887397},
    version      = {v1.0.2}
}
```

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