Practical Methods for Constructing Possibility Distributions

Dubois, D; Prade, H

Practical Methods for Constructing Possibility Distributions

Dubois, D Prade, H

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Publication Type:: Journal Article
Citation:: International Journal of Intelligent Systems, 2016, 31 (3), pp. 215 - 239
Issue Date:: 2016-03-01

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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.date.issued	2016-03-01	en_US
dc.identifier.citation	International Journal of Intelligent Systems, 2016, 31 (3), pp. 215 - 239	en_US
dc.identifier.issn	0884-8173	en_US
dc.identifier.uri	http://hdl.handle.net/10453/118733
dc.description.abstract	© 2015 Wiley Periodicals, Inc. This survey paper provides an overview of existing methods for building possibility distributions. We both consider the case of qualitative possibility theory, where the scale remains ordinal, and the case of quantitative possibility theory, where the scale is the real interval [0, 1]. Methods may be order-based or similarity-based for qualitative possibility distributions, whereas statistical methods apply in the quantitative case and then possibilities encode nested random epistemic sets or upper bounds of probabilities. But distance-based approaches, or expert estimates, may be also exploited in the quantitative case.	en_US
dc.relation.ispartof	International Journal of Intelligent Systems	en_US
dc.relation.isbasedon	10.1002/int.21782	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Practical Methods for Constructing Possibility Distributions	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	31	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	1702 Cognitive Sciences	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.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	31	en_US

Abstract:

© 2015 Wiley Periodicals, Inc. This survey paper provides an overview of existing methods for building possibility distributions. We both consider the case of qualitative possibility theory, where the scale remains ordinal, and the case of quantitative possibility theory, where the scale is the real interval [0, 1]. Methods may be order-based or similarity-based for qualitative possibility distributions, whereas statistical methods apply in the quantitative case and then possibilities encode nested random epistemic sets or upper bounds of probabilities. But distance-based approaches, or expert estimates, may be also exploited in the quantitative case.

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http://hdl.handle.net/10453/118733