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Binarization Algorithms for Approximate Updating in Credal Nets
 

Summary: Binarization Algorithms for Approximate
Updating in Credal Nets
Alessandro Antonucci a,1
, Marco Zaffalon a
, Jaime S. Ide b
and Fabio G. Cozman c
a
Istituto Dalle Molle di Studi sull'Intelligenza Artificiale
Galleria 2 - 6928 Manno (Lugano), Switzerland
b
Escola de Economia de S~ao Paulo, Fundac¸ao Getulio Vargas
Rua Itapeva, 474 - S~ao Paulo, SP - Brazil
c
Escola Politecnica, Universidade de S~ao Paulo
Av. Prof. Mello Moraes, 2231 - S~ao Paulo, SP - Brazil
Abstract. Credal networks generalize Bayesian networks relaxing numerical pa-
rameters. This considerably expands expressivity, but makes belief updating a hard
task even on polytrees. Nevertheless, if all the variables are binary, polytree-shaped
credal networks can be efficiently updated by the 2U algorithm. In this paper we
present a binarization algorithm, that makes it possible to approximate an updat-

  

Source: Antonucci, Alessandro - Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA)
Zaffalon, Marco - Istituto Dalle Molle di Studi sull' Intelligenza Artificiale (IDSIA)

 

Collections: Computer Technologies and Information Sciences