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Generalized Loopy 2U: A New Algorithm for Approximate Inference in Credal Networks
 

Summary: Generalized Loopy 2U: A New Algorithm for
Approximate Inference in Credal Networks
Alessandro Antonucci,a
, Yi Suna
, Cassio P. de Camposa
, Marco Zaffalona
a
IDSIA, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale,
Galleria 2, CH-6928 Manno (Lugano), Switzerland
Abstract
Credal networks generalize Bayesian networks by relaxing the requirement
of precision of probabilities. Credal networks are considerably more expres-
sive than Bayesian networks, but this makes belief updating NP-hard even
on polytrees. We develop a new efficient algorithm for approximate belief
updating in credal networks. The algorithm is based on an important repre-
sentation result we prove for general credal networks: that any credal network
can be equivalently reformulated as a credal network with binary variables;
moreover, the transformation, which is considerably more complex than in
the Bayesian case, can be implemented in polynomial time. The equivalent
binary credal network is then updated by L2U, a loopy approximate algo-

  

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

 

Collections: Computer Technologies and Information Sciences