Evidential Networks from a Different Perspective

0387929 - ÚTIA 2013 RIV DE eng C - Conference Paper (international conference)
Vejnarová, Jiřina
Evidential Networks from a Different Perspective.
Synergies of Soft Computing and Statistics for Intelligent Data Analysis. Heidelberg: Springer, 2012 - (Kruse, R.; Berthold, M.; Moewes, C.; Gil, M.; Grzegorzewski, P.; Hryniewicz, O.), s. 429-436. Advances in Intelligent Systems and Computing, 190. ISBN 978-3-642-33041-4.
[Soft Methods In Probability and Statistics. Konstanz (DE), 04.10.2012-06.10.2012]
R&D Projects: GA ČR GAP402/11/0378
Institutional support: RVO:67985556
Keywords : evidence theory * conditioning * conditional independence * evidential networks
Subject RIV: BA - General Mathematics
http://library.utia.cas.cz/separaty/2013/MTR/vejnarova-evidential networks from a different perspective.pdf

Bayesian networks are, at present, probably the most popular representative of so-called graphical Markov models. Naturally, several attempts to construct an analogy of Bayesian networks have also been made in other frameworks as e.g. in possibility theory, evidence theory or in more general frameworks of valuation-based systems and credal sets. We collect previously obtained results concerning conditioning, conditional independence and irrelevance allowing to define a new type of evidential networks, based on conditional basic assignments. These networks can be seen as a generalization of Bayesian networks, however, they are less powerful than e.g. so-called compositional models, as we demonstrate by a simple example.
Permanent Link: http://hdl.handle.net/11104/0217945