Title :
Evaluation of qualitative possibilistic influence diagrams using strong junction trees
Author :
Essghaier, Fatma ; Ben Amor, Nahla ; Fargier, Helene
Author_Institution :
LARODEC, Inst. Super. de Gestion de Tunis, Le Bardo, Tunisia
Abstract :
Possibilistic influence diagrams are decision graphical models in the possibilistic framework [1]. They present an alliance between decision theory, graph theory and possibilistic theory, in order to represent decision problems and define their optimal strategy through evaluation algorithms. In this paper we present a new approach to evaluate qualitative influence diagrams.
Keywords :
decision theory; optimisation; possibility theory; trees (mathematics); decision graphical model; decision problem representation; decision theory; evaluation algorithm; graph theory; optimal strategy; possibilistic framework; possibilistic theory; qualitative influence diagram; qualitative possibilistic influence diagram; strong junction trees; Absorption; Context; Decision trees; Junctions; Particle separators; Probabilistic logic; Uncertainty; Possibilistic influence diagrams; decision theory; qualitative utilities;
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2013 5th International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-5812-5
DOI :
10.1109/ICMSAO.2013.6552645
