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Tutorial on basic reinforcement learning concepts

DOI License: GPL v3

Material for this tutorial

Citing the tutorial

@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}
}

Download the repository

Get the repository with Git

You will need to have Git previously installed in your computer. To check if you have it installed, open your terminal and type:

git --version

Git installation in MacOS

brew update
brew install git

Git installation in Linux

In Ubuntu/Debian

sudo apt install git

In CentOS

sudo yum install git

Once 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-learning

Getting started

You need to install the dependencies before running the notebooks.

Using conda

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

Running the tutorial

After installing the package

You can start the jupyter notebook in the terminal, and it will start a browser automatically

python -m jupyter notebook

Alternatively, you can use supported Editor to run the jupyter notebooks, e.g. with VS Code.

Jupyter Notebooks

Use cmd+Enter to execute one cell block

Part 1 Simple Gridworld (no ML libraries)

The first part of the tutorial is in RL_simple_gridworld.ipynb.

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