A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics
Abstract
This paper introduces the rllib as an original C++ template-based library oriented toward value function estimation. Generic programming is promoted here as a way of having a good fit between the mathematics of reinforcement learning and their implementation in a library. The main concepts of rllib are presented, as well as a short example.
Cite
Text
Frezza-Buet and Geist. "A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics." Machine Learning Open Source Software, 2013.Markdown
[Frezza-Buet and Geist. "A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics." Machine Learning Open Source Software, 2013.](https://mlanthology.org/mloss/2013/frezzabuet2013jmlr-templatebased/)BibTeX
@article{frezzabuet2013jmlr-templatebased,
title = {{A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics}},
author = {Frezza-Buet, Hervé and Geist, Matthieu},
journal = {Machine Learning Open Source Software},
year = {2013},
pages = {625-628},
volume = {14},
url = {https://mlanthology.org/mloss/2013/frezzabuet2013jmlr-templatebased/}
}