A comparison of evidential networks and compositional models

Jiřina Vejnarová

Kybernetika (2014)

  • Volume: 50, Issue: 2, page 246-267
  • ISSN: 0023-5954

Abstract

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Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example, we will show a problem appearing in this model caused by the use of a conditioning rule. We will also show that this problem can be avoided if undirected or compositional models are used instead.

How to cite

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Vejnarová, Jiřina. "A comparison of evidential networks and compositional models." Kybernetika 50.2 (2014): 246-267. <http://eudml.org/doc/261863>.

@article{Vejnarová2014,
abstract = {Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example, we will show a problem appearing in this model caused by the use of a conditioning rule. We will also show that this problem can be avoided if undirected or compositional models are used instead.},
author = {Vejnarová, Jiřina},
journal = {Kybernetika},
keywords = {evidence theory; conditioning; independence; directed graphs; evidence theory; conditioning; independence; directed graphs},
language = {eng},
number = {2},
pages = {246-267},
publisher = {Institute of Information Theory and Automation AS CR},
title = {A comparison of evidential networks and compositional models},
url = {http://eudml.org/doc/261863},
volume = {50},
year = {2014},
}

TY - JOUR
AU - Vejnarová, Jiřina
TI - A comparison of evidential networks and compositional models
JO - Kybernetika
PY - 2014
PB - Institute of Information Theory and Automation AS CR
VL - 50
IS - 2
SP - 246
EP - 267
AB - Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example, we will show a problem appearing in this model caused by the use of a conditioning rule. We will also show that this problem can be avoided if undirected or compositional models are used instead.
LA - eng
KW - evidence theory; conditioning; independence; directed graphs; evidence theory; conditioning; independence; directed graphs
UR - http://eudml.org/doc/261863
ER -

References

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