Advances in Artificial Intelligence - IBERAMIA-SBIA 2006

Volume 4140 of the series Lecture Notes in Computer Science pp 612-621

Probabilistic Logic with Strong Independence

  • Fabio G. CozmanAffiliated withEscola Politécnica, Univ. de São Paulo
  • , Cassio P. de CamposAffiliated withEscola Politécnica, Univ. de São PauloUniv. Mackenzie
  • , José Carlos F. da RochaAffiliated withUniv. Estadual de Ponta Grossa

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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.