Learning non probabilistic belief networks

  • Luis M. de Campos
  • Juan F. Huete
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 747)


Probability intervals constitute an interesting formalism for representing uncertainty. In order to use them together with belief networks, we study basic concepts as marginalization, conditioning and independence for probability intervals. Then we develop some algorithms for learning simple belief networks (trees and polytrees), based on this kind of non purely probabilistic information.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Luis M. de Campos
    • 1
  • Juan F. Huete
    • 1
  1. 1.Departamento de Ciencias de la Computación e I.A.Universidad de GranadaGranadaSpain

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