Inferring Quantitative Preferences: Beyond Logical Deduction

In this paper we consider a hybrid possibilistic-probabilistic alternative approach to Probabilistic Preference Logic Networks (PPLNs). Namely, we first adopt a possibilistic model to represent the beliefs about uncertain strict preference statements, and then, by means of a pignistic probability tr...

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Bibliographic Details
Published inScalable Uncertainty Management pp. 387 - 395
Main Authors Martinez, Maria Vanina, Godo, Lluis, Simari, Gerardo I.
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Necessity degrees
Possibilistic logic
Preferences
Probabilistic transformation
Tractable approximation
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Summary:In this paper we consider a hybrid possibilistic-probabilistic alternative approach to Probabilistic Preference Logic Networks (PPLNs). Namely, we first adopt a possibilistic model to represent the beliefs about uncertain strict preference statements, and then, by means of a pignistic probability transformation, we switch to a probabilistic-based credulous inference of new preferences for which no explicit (or transitive) information is provided. Finally, we provide a tractable approximate method to compute these probabilities.
ISBN:9783030004606
3030004600
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-030-00461-3_29