A comparison of Lauritzen-Spiegelhalter, HUGIN, and Shenoy-Shafer architectures for computi.pdf
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A comparison of Lauritzen-Spiegelhalter, HUGIN, and Shenoy-Shafer architectures for computi
A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer
Architectures for Computing Marginals of Probability Distributions
Vasilica Lepar Prakash P. Shenoy
Institute of Informatics School of Business
University of Fribourg University of Kansas
Site Regina Mundi, Rue Faucigny 2 Summerfield Hall
CH-1700, Fribourg, Switzerland Lawrence, KS 66045-2003, USA
vasilica.lepar@unifr.ch pshenoy@ukans.edu
Abstract
In the last decade, several architectures have been
proposed for exact computation of marginals us-
ing local computation. In this paper, we compare
three architectures—Lauritzen-Spiegelhalter,
Hugin, and Shenoy-Shafer—from the perspective
of graphical structure for message propagation,
message-passing scheme, computational effi-
ciency, and storage efficiency.
1 INTRODUCTION
In the last decade, several architectures have been proposed
in the uncertain reasoning literature for exact computation
of marginals of multivariate discrete probability distribu-
tions. One of the pioneering architectures for computing
marginals was proposed by Pearl [1986]. Pearl’s architec-
ture applies to singly connected Bayes nets. For multiply
connected Bayes nets, Pearl [1986] proposed the method of
conditioning to reduce a multiply connected Bayes net to
several singly connected Bayes nets.
In 1988, Lauritzen and Spiegelhalter [1988] proposed an
alternative architecture for computing marginals that ap-
plies to any Bayes net. Subsequently, Jensen et al.
[1990a, b] proposed a modification of the Lauritzen-
Spiegelhalter architecture. We call this architecture the
Hugin architecture since this architecture is implemented
in Hugin, a software tool developed by the same group.
Recently, this architecture has been abstracted by Lau-
ritzen and Jensen [1996] so that it applies more generally
to other domains including the Dempster-Shafer’s belief
function theory.
Inspired by the work of Pearl, Shenoy and Shafer [1986]
first adapted and generalized Pearl’s architecture to the case
o
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