@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.}
}