CP-nets: A tool for representing and reasoning with conditional ceteris paribus preference statements

Craig Boutilier, Ronen I. Brafman, Carmel Domshlak, Holger H. Hoos, David Poole

Research output: Contribution to journalReview articlepeer-review

755 Scopus citations

Abstract

Information about user preferences plays a key role in automated decision making. In many domains it is desirable to assess such preferences in a qualitative rather than quantitative way. In this paper, we propose a qualitative graphical representation of preferences that reflects conditional dependence and independence of preference statements under a ceteris paribus (all else being equal) interpretation. Such a representation is often compact and arguably quite natural in many circumstances. We provide a formal semantics for this model, and describe how the structure of the network can be exploited in several inference tasks, such as determining whether one outcome dominates (is preferred to) another, ordering a set outcomes according to the preference relation, and constructing the best outcome subject to available evidence.

Original languageEnglish
Pages (from-to)135-191
Number of pages57
JournalJournal Of Artificial Intelligence Research
Volume21
DOIs
StatePublished - 1 Jan 2004

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'CP-nets: A tool for representing and reasoning with conditional ceteris paribus preference statements'. Together they form a unique fingerprint.

Cite this