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
Link To Document