@inproceedings{vanseijen2013efficient,
author = {van Seijen, Harm and Whiteson, Shimon and Kester, L.J.H.M.},
title = {Efficient Abstraction Selection in Reinforcement Learning – Extended Abstract},
booktitle = {SARA'13},
year = {2013},
month = {July},
abstract = {This paper introduces a novel approach for abstraction selection in reinforcement learning problems modelled as factored Markov decision processes (MDPs), for which a state is described via a set of state components. In abstraction selection, an agent must choose an abstraction from a set of candidate abstractions, each build up from a different combination of state components.},
url = {http://approjects.co.za/?big=en-us/research/publication/efficient-abstraction-selection-reinforcement-learning-extended-abstract/},
edition = {SARA'13},
}