Conditional preference nets and possibilistic logic

Dubois, D; Prade, H; Touazi, F

Conditional preference nets and possibilistic logic

Dubois, D Prade, H

Touazi, F

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 7958 LNAI pp. 181 - 193
Issue Date:: 2013-08-01

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Field	Value	Language
dc.contributor.author	Dubois, D	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.contributor.author	Touazi, F	en_US
dc.date.issued	2013-08-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 7958 LNAI pp. 181 - 193	en_US
dc.identifier.isbn	9783642390906	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32840
dc.description.abstract	CP-nets (Conditional preference networks) are a well-known compact graphical representation of preferences in Artificial Intelligence, that can be viewed as a qualitative counterpart to Bayesian nets. In case of binary attributes it captures specific partial orderings over Boolean interpretations where strict preference statements are defined between interpretations which differ by a single flip of an attribute value. It respects preferential independence encoded by the ceteris paribus property. The popularity of this approach has motivated some comparison with other preference representation setting such as possibilistic logic. In this paper, we focus our discussion on the possibilistic representation of CP-nets, and the question whether it is possible to capture the CP-net partial order over interpretations by means of a possibilistic knowledge base and a suitable semantics. We show that several results in the literature on the alleged faithful representation of CP-nets by possibilistic bases are questionable. To this aim we discuss some canonical examples of CP-net topologies where the considered possibilistic approach fails to exactly capture the partial order induced by CP-nets, thus shedding light on the difficulties encountered when trying to reconcile the two frameworks. © 2013 Springer-Verlag Berlin Heidelberg.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-39091-3-16	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Conditional preference nets and possibilistic logic	en_US
dc.type	Conference Proceeding
utslib.citation.volume	7958 LNAI	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	7958 LNAI	en_US

Abstract:

CP-nets (Conditional preference networks) are a well-known compact graphical representation of preferences in Artificial Intelligence, that can be viewed as a qualitative counterpart to Bayesian nets. In case of binary attributes it captures specific partial orderings over Boolean interpretations where strict preference statements are defined between interpretations which differ by a single flip of an attribute value. It respects preferential independence encoded by the ceteris paribus property. The popularity of this approach has motivated some comparison with other preference representation setting such as possibilistic logic. In this paper, we focus our discussion on the possibilistic representation of CP-nets, and the question whether it is possible to capture the CP-net partial order over interpretations by means of a possibilistic knowledge base and a suitable semantics. We show that several results in the literature on the alleged faithful representation of CP-nets by possibilistic bases are questionable. To this aim we discuss some canonical examples of CP-net topologies where the considered possibilistic approach fails to exactly capture the partial order induced by CP-nets, thus shedding light on the difficulties encountered when trying to reconcile the two frameworks. © 2013 Springer-Verlag Berlin Heidelberg.

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http://hdl.handle.net/10453/32840