0481260 20240103214928.420171113235959.9 84951199230 000374614900006 10.1016/j.ijar.2015.10.003 18 s. P cav_un_epca*02567740888-613X721 (2016)95-112Elsevier operator of composition causality belief function cav_un_auth*0101118 Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory 50 Jiroušek Radim UTIA-B K Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0275452 Shenoy P. P. US http://library.utia.cas.cz/separaty/2017/MTR/jirousek-0481260.pdf cav_un_auth*0353428 GA15-00215S GA ČR CZ The paper shows that Pearl’s causal networks can be described using causal compositional models (CCMs) in the valuation-based systems (VBS) framework. One major advantage of using the VBS framework is that as VBS is a generalization of several uncertainty theories (e.g., probability theory, a version of possibility theory where combination is the product t-norm, Spohn’s epistemic belief theory, and Dempster–Shafer belief function theory), CCMs, initially described in probability theory, are now described in all uncertainty calculi that fit in the VBS framework. We describe conditioning and interventions in CCMs. AH 50000 50200 50201 2018 2 RVO:67985556 http://hdl.handle.net/11104/0277012 cav_un_auth*0353270 School of Business, University of Kansas, Lawrence US S 3+4 Article|Proceedings Paper Computer Science Artificial Intelligence COMPUTERSCIENCE.ARTIFICIALINTELLIGENCE 2.948 0.625 7.4 0.00519 0.785 3341 1.275 Q1 2.337 96 Q2 65.62 74.8 Q2 Q1 74.812 2016 84951199230 SCOPUS PUBMED 000374614900006 WOS cav_un_epca*0256774 International Journal of Approximate Reasoning 0888-613X 1873-4731 Roč. 72 č. 1 2016 95 112 Elsevier