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 (\(\pi \)-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 \(\pi \)-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 \(\pi \)-pref nets is polynomial.
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Notes
- 1.
If a variable has only one element in its domain, it is a constant, and we could remove it if we wished.
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Acknowledgements
This material is based upon works supported by the Science Foundation Ireland under Grants No. 12/RC/2289 and No. 12/RC/2289-P2 which are co-funded under the European Regional Development Fund.
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Wilson, N., Dubois, D., Prade, H. (2019). CP-Nets, \(\pi \)-pref Nets, and Pareto Dominance. In: Ben Amor, N., Quost, B., Theobald, M. (eds) Scalable Uncertainty Management. SUM 2019. Lecture Notes in Computer Science(), vol 11940. Springer, Cham. https://doi.org/10.1007/978-3-030-35514-2_13
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