Probabilistic Logic with Strong Independence

  • Fabio G. Cozman
  • Cassio P. de Campos
  • José Carlos F. da Rocha
Conference paper

DOI: 10.1007/11874850_65

Volume 4140 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Cozman F.G., de Campos C.P., da Rocha J.C.F. (2006) Probabilistic Logic with Strong Independence. In: Sichman J.S., Coelho H., Rezende S.O. (eds) Advances in Artificial Intelligence - IBERAMIA-SBIA 2006. Lecture Notes in Computer Science, vol 4140. Springer, Berlin, Heidelberg

Abstract

This papers investigates the manipulation of statements of strong independence in probabilistic logic. Inference methods based on polynomial programming are presented for strong independence, both for unconditional and conditional cases. We also consider graph-theoretic representations, where each node in a graph is associated with a Boolean variable and edges carry a Markov condition. The resulting model generalizes Bayesian networks, allowing probabilistic assessments and logical constraints to be mixed.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fabio G. Cozman
    • 1
  • Cassio P. de Campos
    • 1
    • 2
  • José Carlos F. da Rocha
    • 3
  1. 1.Escola PolitécnicaUniv. de São PauloSão PauloBrazil
  2. 2.Univ. MackenzieSão PauloBrazil
  3. 3.Univ. Estadual de Ponta GrossaPonta GrossaBrazil