Learning Ordinal Preferences on Multiattribute Domains: The Case of CP-nets

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Reference

Yann Chevaleyre, Frédéric Koriche, Jérôme Lang, Jérôme Mengin, Bruno Zanuttini: Learning Ordinal Preferences on Multiattribute Domains: The Case of CP-nets. In: Fürnkranz, J. and Hüllermeier, E.: Preference Learning, 2011, 273-296.

DOI

http://dx.doi.org/10.1007/978-3-642-14125-6_13

Abstract

A recurrent issue in decision making is to extract a preference structure by observing the user’s behavior in different situations. In this paper, we investigate the problem of learning ordinal preference orderings over discrete multiattribute, or combinatorial, domains. Specifically, we focus on the learnability issue of conditional preference networks, or CP-nets, that have recently emerged as a popular graphical language for representing ordinal preferences in a concise and intuitive manner. This paper provides results in both passive and active learning. In the passive setting, the learner aims at finding a CP-net compatible with a supplied set of examples, while in the active setting the learner searches for the cheapest interaction policy with the user for acquiring the target CP-net.

Extended Abstract

Bibtex

@incollection{
year={2011},
isbn={978-3-642-14124-9},
booktitle={Preference Learning},
editor={Fürnkranz, Johannes and Hüllermeier, Eyke},
doi={10.1007/978-3-642-14125-6_13},
title={Learning Ordinal Preferences on Multiattribute Domains: The Case of CP-nets},
url={http://dx.doi.org/10.1007/978-3-642-14125-6_13, http://de.evo-art.org/index.php?title=Learning_Ordinal_Preferences_on_Multiattribute_Domains:_The_Case_of_CP-nets },
publisher={Springer Berlin Heidelberg},
author={Chevaleyre, Yann and Koriche, Frédéric and Lang, Jérôme and Mengin, Jérôme and Zanuttini, Bruno},
pages={273-296},
language={English}
}

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