• DocumentCode
    1030354
  • Title

    Non-causal versus causal qualitative modelling and simulation

  • Author

    Travé-Massuyès, Louise ; Bousson, Kouamana ; Evrard, Jean-Michel ; Guerrin, Frangois ; Lucas, Bruno ; Missier, Antoine ; Tomasena, Miguel ; Zimmer, Laurent

  • Author_Institution
    Lab. d´´Autom. et d´´Anal. des Syst., CNRS, Toulouse, France
  • Volume
    2
  • Issue
    3
  • fYear
    1993
  • Firstpage
    159
  • Lastpage
    182
  • Abstract
    Qualitative models of dynamical systems fall into noncausal or causal approaches. The noncausal approach is widely used in part because traditional physics describes phenomena by means of symmetric functional relations. It supports the idea that causality can be ignored or inferred from the model itself. Nevertheless, when people explain how things work, they use causal relations. Representing causality explicitly makes it possible to take advantage of exogenous knowledge necessary for understanding the phenomena and supporting self-explanatory simulation. The basic concepts used in both approaches, in addition to the representation formalisms and algorithms, are discussed
  • Keywords
    case-based reasoning; knowledge representation; modelling; causal qualitative modelling; exogenous knowledge; noncausal qualitative modelling; qualitative simulation; self-explanatory simulation; symmetric functional relations;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems Engineering
  • Publisher
    iet
  • ISSN
    0963-9640
  • Type

    jour

  • Filename
    265861