0387908 20240103202028.620130207235959.9 000312034100029 10.1007/978-3-642-29461-7_29 8 s. P cav_un_epca*0379833978-3-642-29460-01867-5662247-254HeidelbergSpringer2012DenoeuxT.MassonM.H. evidence theory independence cav_un_auth*0101223 Vejnarová Jiřina Matematická teorie rozhodování Department of Decision Making Theory MTR MTR UTIA-B Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2013/MTR/vejnarova-on random sets independence and strong independence in evidence theory.pdf GAP402/11/0378 GA ČR cav_un_auth*0273630 Belief and plausibility functions can be viewed as lower and upper probabilities possessing special properties. Therefore, (conditional) independence concepts from the framework of imprecise probabilities can also be applied to its sub-framework of evidence theory. In this paper we concentrate ourselves on random sets independence, which seems to be a natural concept in evidence theory, and strong independence, one of two principal concepts (together with epistemic independence) in the framework of credal sets. We show that application of trong independence to two bodies of evidence generally leads to a model which is Beyond the framework of evidence theory. Nevertheless, if we add a condition on resulting focal elements, then strong independence reduces to random sets independence. Unfortunately, it is not valid no more for conditional independence. cav_un_auth*0288295 2nd International Conference on Belief Functions Compiegne 09.05.2012-11.05.2012 FR 2013 BA 1 PR RVO:67985556 http://hdl.handle.net/11104/0217947 0.126 Q4 Q4 2012 000312034100029 WOS cav_un_epca*0379833 Belief Functions: Theory and Applications 978-3-642-29460-0 1867-5662 247 254 Heidelberg Springer 2012 Advances in Intelligent and Soft Computing 164 Denoeux T. 340 Masson M.H. 340