Geodesic
A comparison of evidential networks and compositional models
Kybernetika, Tome 50 (2014) no. 2, pp. 246-267

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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.
DOI : 10.14736/kyb-2014-2-0246
Classification : 62H17, 62H99, 68T37
Keywords: evidence theory; conditioning; independence; directed graphs 
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Vejnarová, Jiřina. A comparison of evidential networks and compositional models. Kybernetika, Tome 50 (2014) no. 2, pp. 246-267. doi: 10.14736/kyb-2014-2-0246

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