ICIC   25583
INSTITUTO DE CIENCIAS E INGENIERIA DE LA COMPUTACION
Unidad Ejecutora - UE
capítulos de libros
Título:
Inferring Quantitative Preferences: Beyond Logical Deduction
Autor/es:
MARIA VANINA MARTINEZ; GERARDO I. SIMARI; LLUIS GODO
Libro:
Scalable Uncertainty Management - 12th International Conference
Editorial:
Springer
Referencias:
Lugar: Cham; Año: 2018; p. 387 - 395
Resumen:
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.