Kybernetika 50 no. 2, 246-267, 2014

A comparison of evidential networks and compositional models

Jiřina VejnarováDOI: 10.14736/kyb-2014-2-0246


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.


conditioning, independence, evidence theory, directed graphs




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