Merging conflicting propositional knowledge by similarity

Schockaert, S; Prade, H

Merging conflicting propositional knowledge by similarity

Schockaert, S Prade, H

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, 2009, pp. 224 - 228
Issue Date:: 2009-12-01

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Field	Value	Language
dc.contributor.author	Schockaert, S	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.date.issued	2009-12-01	en_US
dc.identifier.citation	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, 2009, pp. 224 - 228	en_US
dc.identifier.isbn	9781424456192	en_US
dc.identifier.issn	1082-3409	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32877
dc.description.abstract	The paper discusses a new approach to merging conflicting propositional knowledge bases which builds on the idea that consistency can often be restored by interpreting propositions more flexibly, thus enlarging their sets of models. © 2009 IEEE.	en_US
dc.relation.ispartof	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI	en_US
dc.relation.isbasedon	10.1109/ICTAI.2009.56	en_US
dc.title	Merging conflicting propositional knowledge by similarity	en_US
dc.type	Conference Proceeding
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

Abstract:

The paper discusses a new approach to merging conflicting propositional knowledge bases which builds on the idea that consistency can often be restored by interpreting propositions more flexibly, thus enlarging their sets of models. © 2009 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/32877