0558135 20230316105120.020220613235959.9 Computing the Decomposable Entropy of Graphical Belief Function Models 12 s. P cav_un_epca*0558134978-80-7378-460-7Proceedings of the 12th Workshop on Uncertainty Processing111-122PragueMatfyzPress2022StudenýMilanAyNihatColettiGiulianellaKleiterGernot D.ShenoyPrakash P. Decomposable Entropy DempsterShafer belief functions Bayesian networks cav_un_auth*0101118 Jiroušek Radim UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0216188 Kratochvíl Václav UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0275452 Shenoy P. P. US http://library.utia.cas.cz/separaty/2022/MTR/kratochvil-0558135.pdf GA19-04579S GA ČR CZ cav_un_auth*0380558 GA19-06569S GA ČR CZ cav_un_auth*0380559 In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief functions called decomposable entropy. Here, we provide an algorithm for computing the decomposable entropy of directed graphical D-S belief function models. For undirected graphical belief function models, assuming that each belief function in the model is non-informative to the others, no algorithm is necessary. We compute the entropy of each belief function and add them together to get the decomposable entropy of the model. Finally, the decomposable entropy generalizes Shannon’s entropy not only for the probability of a single random variable but also for multinomial distributions expressed as directed acyclic graphical models called Bayesian networks. cav_un_auth*0431432 WUPES 2022: 12th Workshop on Uncertainty Processing 20220601 20220604 Kutná Hora CZ BA 10000 10100 10102 2023 3 PR RVO:67985556 http://hdl.handle.net/11104/0332321 S 2022 SCOPUS PUBMED WOS cav_un_epca*0558134 Proceedings of the 12th Workshop on Uncertainty Processing MatfyzPress 2022 Prague 111 122 978-80-7378-460-7 Studený Milan 340 Ay Nihat 340 Coletti Giulianella 340 Kleiter Gernot D. 340 Shenoy Prakash P. 340