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Representing and reasoning with qualitative preferences : = tools and applications /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Representing and reasoning with qualitative preferences :/ Ganesh Ram Santhanam, Iowa State University ; Samik Basu, Iowa State University ; Vasant Honavar, Pennsylvania State University
Reminder of title:	tools and applications /
Author:	Santhanam, Ganesh Ram,
other author:	Basu, Samik,
Description:	1 online resource (xv, 138 pages) :illustrations :
Subject:	Qualitative research -
Online resource:	http://portal.igpublish.com/iglibrary/search/MCPB0000815.html
ISBN:	9781627058407$q(electronic bk.)

Representing and reasoning with qualitative preferences : = tools and applications /
Santhanam, Ganesh Ram,

Representing and reasoning with qualitative preferences :tools and applications /Ganesh Ram Santhanam, Iowa State University ; Samik Basu, Iowa State University ; Vasant Honavar, Pennsylvania State University - 1 online resource (xv, 138 pages) :illustrations - Synthesis lectures on artificial intelligence and machine learning,#311939-4616 ;. - Synthesis lectures on artificial intelligence and machine learning ;29.

Includes bibliographical references (pages 127-135)

Qualitative preferences -- Qualitative preference languages -- Model checking and computation tree logic -- Dominance testing via model checking -- Verifying preference equivalence and subsumption -- Ordering alternatives with respect to preference - - CRISNER: a practically efficient reasoner for qualitative preferences -- Postscript

This book provides a tutorial introduction to modern techniques for representing and reasoning about qualitative preferences with respect to a set of alternatives. The syntax and semantics of several languages for representing preference languages, including CP-nets, TCP-nets, CI-nets, and CP-theories, are reviewed. Some key problems in reasoning about preferences are introduced, including determining whether one alternative is preferred to another, or whether they are equivalent, with respect to a given set of preferences. These tasks can be reduced to model checking in temporal logic. Specifically, an induced preference graph that represents a given set of preferences can be efficiently encoded using a Kripke Structure for Computational Tree Logic (CTL). One can translate preference queries with respect to a set of preferences into an equivalent set of formulae in CTL, such that the CTL formula is satisfied whenever the preference query holds

ISBN: 9781627058407$q(electronic bk.)

Standard No.: 10.2200 / S00689ED1V01Y201512AIM031doiSubjects--Topical Terms:

657527
Qualitative research
Subjects--Index Terms:

preferencesIndex Terms--Genre/Form:

761329
Electronic books

LC Class. No.: Q387 / .S267 2016

Dewey Class. No.: 006.332

Representing and reasoning with qualitative preferences : = tools and applications /
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245 1 0 $a Representing and reasoning with qualitative preferences : $b tools and applications / $c Ganesh Ram Santhanam, Iowa State University ; Samik Basu, Iowa State University ; Vasant Honavar, Pennsylvania State University
264 1 $a San Rafael, California : $b Morgan & Claypool Publishers, $c [2016]
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300 $a 1 online resource (xv, 138 pages) : $b illustrations
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490 0 $a Synthesis lectures on artificial intelligence and machine learning, $x 1939-4616 ; $v #31
504 $a Includes bibliographical references (pages 127-135)
505 0 $a Qualitative preferences -- Qualitative preference languages -- Model checking and computation tree logic -- Dominance testing via model checking -- Verifying preference equivalence and subsumption -- Ordering alternatives with respect to preference - - CRISNER: a practically efficient reasoner for qualitative preferences -- Postscript
520 $a This book provides a tutorial introduction to modern techniques for representing and reasoning about qualitative preferences with respect to a set of alternatives. The syntax and semantics of several languages for representing preference languages, including CP-nets, TCP-nets, CI-nets, and CP-theories, are reviewed. Some key problems in reasoning about preferences are introduced, including determining whether one alternative is preferred to another, or whether they are equivalent, with respect to a given set of preferences. These tasks can be reduced to model checking in temporal logic. Specifically, an induced preference graph that represents a given set of preferences can be efficiently encoded using a Kripke Structure for Computational Tree Logic (CTL). One can translate preference queries with respect to a set of preferences into an equivalent set of formulae in CTL, such that the CTL formula is satisfied whenever the preference query holds
520 $a This allows us to use a model checker to reason about preferences, i.e., answer preference queries, and to obtain a justification as to why a preference query is satisfied (or not) with respect to a set of preferences. This book defines the notions of the equivalence of two sets of preferences, including what it means for one set of preferences to subsume another, and shows how to answer preferential equivalence and subsumption queries using model checking. Furthermore, this book demonstrates how to generate alternatives ordered by preference, along with providing ways to deal with inconsistent preference specifications. A description of CRISNER.an open source software implementation of the model checking approach to qualitative preference reasoning in CP-nets, TCP-nets, and CP-theories is included, as well as examples illustrating its use
588 $a Description based on print version record
650 0 $a Qualitative research $3 657527
650 0 $a Knowledge representation (Information theory) $3 567038
650 0 $a Artificial intelligence. $3 559380
653 $a preferences
653 $a qualitative preferences
653 $a preference reasoning
653 $a model checking
653 $a knowledge representation
653 $a automated inference
653 $a decision support systems
655 0 $a Electronic books $2 local. $3 761329
700 1 $a Basu, Samik, $e author $3 1175742
700 1 $a Honavar, Vasant, $e author $3 1175743
830 0 $a Synthesis lectures on artificial intelligence and machine learning ; $v 29 $3 1136768
856 4 0 $u http://portal.igpublish.com/iglibrary/search/MCPB0000815.html