Towards analogy-based decision - A proposal

Billingsley, R; Prade, H; Richard, G; Williams, MA

Towards analogy-based decision - A proposal

Billingsley, R Prade, H

Richard, G Williams, MA

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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), 2017, 10333 LNAI pp. 28 - 35
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Billingsley, R	en_US
dc.contributor.author	Prade, H https://orcid.org/0000-0003-4586-8527	en_US
dc.contributor.author	Richard, G	en_US
dc.contributor.author	Williams, MA https://orcid.org/0000-0002-1047-0503	en_US
dc.date.issued	2017-01-01	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, 10333 LNAI pp. 28 - 35	en_US
dc.identifier.isbn	9783319596914	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127655
dc.description.abstract	© Springer International Publishing AG 2017. This short paper outlines an analogy-based decision method. It takes advantage of analogical proportions between situations, i.e., a is to b as c is to d, for proposing plausibly good decisions that may be appropriate for a new situation at hand. It goes beyond case-based decision where the idea of graded similarity may hide some small but crucial differences between situations. The method relies on triples of known cases rather than on individual cases for making a prediction on the appropriateness of a potential decision, or for proposing a way of adapting a decision according to situations. The approach may be of interest in a variety of problems ranging from flexible querying systems to cooperative artificial agents.	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	10.1007/978-3-319-59692-1_3	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Towards analogy-based decision - A proposal	en_US
dc.type	Conference Proceeding
utslib.citation.volume	10333 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 Computer Science
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	open_access
pubs.publication-status	Published	en_US
pubs.volume	10333 LNAI	en_US

Abstract:

© Springer International Publishing AG 2017. This short paper outlines an analogy-based decision method. It takes advantage of analogical proportions between situations, i.e., a is to b as c is to d, for proposing plausibly good decisions that may be appropriate for a new situation at hand. It goes beyond case-based decision where the idea of graded similarity may hide some small but crucial differences between situations. The method relies on triples of known cases rather than on individual cases for making a prediction on the appropriateness of a potential decision, or for proposing a way of adapting a decision according to situations. The approach may be of interest in a variety of problems ranging from flexible querying systems to cooperative artificial agents.

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http://hdl.handle.net/10453/127655