• DocumentCode
    614820
  • 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
  • fYear
    2013
  • fDate
    28-30 April 2013
  • Firstpage
    1
  • Lastpage
    6
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modeling, Simulation and Applied Optimization (ICMSAO), 2013 5th International Conference on
  • Conference_Location
    Hammamet
  • Print_ISBN
    978-1-4673-5812-5
  • Type

    conf

  • DOI
    10.1109/ICMSAO.2013.6552645
  • Filename
    6552645