@inproceedings{da9d1cfd00aa4cbface8c84695abe2cd,
title = "CP-Nets, π-pref Nets, and Pareto Dominance",
abstract = "Two approaches have been proposed for the graphical handling of qualitative conditional preferences between solutions described in terms of a finite set of features: Conditional Preference networks (CP-nets for short) and more recently, Possibilistic Preference networks (π-pref nets for short). The latter agree with Pareto dominance, in the sense that if a solution violates a subset of preferences violated by another one, the former solution is preferred to the latter one. Although such an agreement might be considered as a basic requirement, it was only conjectured to hold as well for CP-nets. This non-trivial result is established in the paper. Moreover it has important consequences for showing that π-pref nets can at least approximately mimic CP-nets by adding explicit constraints between symbolic weights encoding the ceteris paribus preferences, in case of Boolean features. We further show that dominance with respect to the extended π-pref nets is polynomial.",
author = "Nic Wilson and Didier Dubois and Henri Prade",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 13th International Conference on Scalable Uncertainty Management, SUM 2019 ; Conference date: 16-12-2019 Through 18-12-2019",
year = "2019",
doi = "10.1007/978-3-030-35514-2\_13",
language = "English",
isbn = "9783030355135",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "169--183",
editor = "\{Ben Amor\}, Nahla and Benjamin Quost and Martin Theobald",
booktitle = "Scalable Uncertainty Management - 13th International Conference, SUM 2019, Proceedings",
address = "United States",
}