Abstract
In this paper we present a two-fold generalization of conditional preference networks (CP-nets) that incorporates uncertainty. CP-nets are a formal tool to model qualitative conditional statements (cp-statements) about preferences over a set of objects. They are inherently static structures, both in their ability to capture dependencies between objects and in their expression of preferences over features of a particular object. Moreover, CP-nets do not provide the ability to express uncertainty over the preference statements. We present and study a generalization of CP-nets which supports changes and allows for encoding uncertainty, expressed in probabilistic terms, over the structure of the dependency links and over the individual preference relations.
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Cornelio, C., Goldsmith, J., Mattei, N., Rossi, F., Venable, K.B. (2013). Updates and Uncertainty in CP-Nets. In: Cranefield, S., Nayak, A. (eds) AI 2013: Advances in Artificial Intelligence. AI 2013. Lecture Notes in Computer Science(), vol 8272. Springer, Cham. https://doi.org/10.1007/978-3-319-03680-9_32
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DOI: https://doi.org/10.1007/978-3-319-03680-9_32
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03679-3
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