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Causal model-based knowledge acquisition tools: Discussion of experiments

  • Jean Charlet
  • Jean-Paul Krivine
  • Chantal Reynaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 599)

Abstract

The aim of this paper is to study causal knowledge and demonstrate how it can be used to support the knowledge acquisition process. The discussion is based on three experiments we have been involved in. First, two classes of Causal Model-Based Knowledge Acquisition Tools are identified: bottom-up designed causal models and top-down designed causal models. The properties of each type of tool and how they contribute to the whole knowledge acquisition process is then discuted.

Keywords

Knowledge Acquisition Causal Model Knowledge Engineer Causal Network Causal Knowledge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Jean Charlet
    • 1
  • Jean-Paul Krivine
    • 2
  • Chantal Reynaud
    • 3
  1. 1.DIAM, INSERM U194 & Service d'Informatique Médicale de l'AP-HPParis Cedex 13France
  2. 2.E.D.F. Direction des Etudes et RecherchesClamart CedexFrance
  3. 3.Laboratoire de Recherche en Informatique, Bât. 490Université Paris-SudOrsay CedexFrance

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