Updates and uncertainty in CP-nets

Cristina Cornelio, Judy Goldsmith, Nicholas Mattei, Francesca Rossi, K. Brent Venable

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 Scopus citations


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.

Original languageEnglish
Title of host publicationAI 2013
Subtitle of host publicationAdvances in Artificial Intelligence - 26th Australasian Joint Conference, Proceedings
Number of pages12
StatePublished - 2013
Event26th Australasian Joint Conference on Artificial Intelligence, AI 2013 - Dunedin, Netherlands
Duration: Dec 1 2013Dec 6 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8272 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference26th Australasian Joint Conference on Artificial Intelligence, AI 2013


  • CP-nets
  • Graphical models
  • Preferences
  • Probabilistic reasoning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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