Andrés Cano, Manuel Gómez, Andrés R. Masegosa, Serafí­n Moral

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Comparing Binary and Standard Probability Trees in Credal Networks Inference

Abstract

This paper proposes the use of Binary Probability Trees in the propagation of credal networks. Standard and binary probability trees are suitable data structures for representing potentials because they allow to control the accuracy of inference algorithms by means of a threshold parameter. The choice of this threshold is a trade-off between accuracy and computing time. Binary trees enable the representation of finer-grained independences than probability trees. This leads to more efficient algorithms for credal networks with variables with more than two states. The paper shows experiments comparing binary and standard probability trees in order to demonstrate their performance.

Keywords

Credal networks, Inference algorithms, Imprecise probabilities, Bayesian networks, Variable elimination, Probability trees

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Authors’ addresses

Andrés Cano
Dpto. Ciencias de la Computación e I.A.
ETS Ingenierías Informática y de Telecomunicación
Avda. Andalucia s/n
Granada 18071
CIF: Q1818002F
Spain

Manuel Gómez
Dpto. Ciencias de la Computación e I.A.
ETS Ingenierías Informática y de Telecomunicación
C// Periodista Daniel Saucedo Aranda
18071 Granada

Andrés R. Masegosa
Departamento de Ciencias de la Computación e Inteligencia Artificial
Escuela Técnica Superior de Ingenierías Informática y de Telecomunicación
c/. Daniel Saucedo Aranda, s/n 18071 Granada

Serafí­n Moral
Dpto. Ciencias de la Computación e IA
ETSI Informática
Universidad de Granada
18071 Granada
SPAIN

E-mail addresses

Andrés Cano		acu@decsai.ugr.es
Manuel Gómez		mgomez@decsai.ugr.es
Andrés R. Masegosa		andrew@decsai.ugr.es
Serafí­n Moral		smc@decsai.ugr.es