@Article{Supelec824,
author = {Hervé Frezza-Buet and Matthieu Geist},
title = {A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics},
journal = {Journal of Machine Learning Research},
year = {2013},
volume = {14},
pages = {625 - 628},
url = {http://jmlr.csail.mit.edu/papers/v14/frezza-buet13a.html},
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 t between the mathematics of reinforcement learning and their implementation in a library. Main concepts of rllib are presented, as well as a short example.}
}