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/}
}