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.
Inferring quantitative preferences: Beyond logical deduction
Martinez M. V.;Simari G. I.
2018-01-01
Abstract
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.File in questo prodotto:
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