-
The theoretical lecture can be found here:
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The tutorial can be found here:
- This tutorial is registered in Zenodo.
- Please use this DOI when citing this material: https://doi.org/10.5281/zenodo.12649046
@software{santamaria_garcia_2024_12649046,
author = {Santamaria Garcia, Andrea},
title = {Tutorial on basic reinforcement learning concepts},
month = jul,
year = 2024,
publisher = {Zenodo},
doi = {10.5281/zenodo.12649046},
url = {https://doi.org/10.5281/zenodo.12649046}
}You will need to have Git previously installed in your computer. To check if you have it installed, open your terminal and type:
git --versionbrew update
brew install gitIn Ubuntu/Debian
sudo apt install gitIn CentOS
sudo yum install gitOnce you have Git installed open your terminal, go to your desired directory, and type:
git clone https://github.com/machine-learning-tutorial/reinforcement-learning
cd reinforcement-learningYou need to install the dependencies before running the notebooks.
If you don't have conda installed already and want to use conda for environment management, you can install the miniconda as described here.
- Create a conda env with
conda create -n rl-tutorial python=3.10 - Activate the environment with
conda activate rl-tutorial - Install the required packages via
pip install -r requirements.txt. - Run the following commands:
python -m jupyter contrib nbextension install --user
python -m jupyter nbextension enable varInspector/main- After the tutorial you can remove your environment with
conda remove -n nn-tutorial --all
After installing the package
You can start the jupyter notebook in the terminal, and it will start a browser automatically
python -m jupyter notebookAlternatively, you can use supported Editor to run the jupyter notebooks, e.g. with VS Code.
Use cmd+Enter to execute one cell block
The first part of the tutorial is in RL_simple_gridworld.ipynb.