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The Complexity of Learning Separable ceteris paribus Preferences

Lang, Jérôme; Mengin, Jérôme (2009), The Complexity of Learning Separable ceteris paribus Preferences, IJCAI-09, 21st International Joint Conference on Artificial Intelligence, AAAI Press / IJCAI : Palo Alto (USA), p. 848-853

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Type
Communication / Conférence
Date
2009
Pays du colloque
UNITED STATES
Titre de l'ouvrage
IJCAI-09, 21st International Joint Conference on Artificial Intelligence
Éditeur
AAAI Press / IJCAI
Ville d’édition
Palo Alto (USA)
Pages
848-853
Métadonnées
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Auteur(s)
Lang, Jérôme
Mengin, Jérôme
Résumé (EN)
We address the problem of learning preference relations on multi-attribute (or combinatorial) domains.We do so by making a very simple hypothesis aboutthe dependence structure between attributes thatthe preference relation enjoys, namely separability(no preferential dependencies between attributes).Given a set of examples consisting of comparisonsbetween alternatives, we want to output a separableCP-net, consisting of local preferences on each ofthe attributes, that fits the examples. We considerthree forms of compatibility between a CP-net anda set of examples, and for each of them we give useful characterizations as well as complexity results.
Mots-clés
Preference relations