0439574 20240903170631.420150120235959.9 84901434883 000337929500006 10.14736/kyb-2014-2-0246 22 s. P cav_un_epca*02971630023-5954502 (2014)246-267Ústav teorie informace a automatizace AV ČR, v. v. i. evidence theory graphical models conditional independence cav_un_auth*0101223 Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory 100 Vejnarová Jiřina UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2014/MTR/vejnarova-0439574.pdf cav_un_auth*0292670 GA13-20012S GA ČR 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. BA 2015 RVO:67985556 http://hdl.handle.net/11104/0242968 S COMPUTERSCIENCECYBERNETICS 0.339 0.369 Q2 42.435 14.583 Q3 Q3 2014 84901434883 SCOPUS 000337929500006 WOS cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 50 č. 2 2014 246 267 Ústav teorie informace a automatizace AV ČR, v. v. i.