MushroomRL: Simplifying Reinforcement Learning Research
Abstract
MushroomRL is an open-source Python library developed to simplify the process of implementing and running Reinforcement Learning (RL) experiments. Compared to other available libraries, MushroomRL has been created with the purpose of providing a comprehensive and flexible framework to minimize the effort in implementing and testing novel RL methodologies. The architecture of MushroomRL is built in such a way that every component of a typical RL experiment is already provided, and most of the time users can only focus on the implementation of their own algorithms. MushroomRL is accompanied by a benchmarking suite collecting experimental results of state-of-the-art deep RL algorithms, and allowing to benchmark new ones. The result is a library from which RL researchers can significantly benefit in the critical phase of the empirical analysis of their works. MushroomRL stable code, tutorials, and documentation can be found at https://github.com/MushroomRL/mushroom-rl.
Cite
Text
D'Eramo et al. "MushroomRL: Simplifying Reinforcement Learning Research." Machine Learning Open Source Software, 2021.Markdown
[D'Eramo et al. "MushroomRL: Simplifying Reinforcement Learning Research." Machine Learning Open Source Software, 2021.](https://mlanthology.org/mloss/2021/deramo2021jmlr-mushroomrl/)BibTeX
@article{deramo2021jmlr-mushroomrl,
title = {{MushroomRL: Simplifying Reinforcement Learning Research}},
author = {D'Eramo, Carlo and Tateo, Davide and Bonarini, Andrea and Restelli, Marcello and Peters, Jan},
journal = {Machine Learning Open Source Software},
year = {2021},
pages = {1-5},
volume = {22},
url = {https://mlanthology.org/mloss/2021/deramo2021jmlr-mushroomrl/}
}