Název:
Computing the Decomposable Entropy of Graphical Belief Function Models
Autoři:
Jiroušek, Radim ; Kratochvíl, Václav ; Shenoy, P. P. Typ dokumentu: Příspěvky z konference Konference/Akce: WUPES 2022: 12th Workshop on Uncertainty Processing, Kutná Hora (CZ), 20220601
Rok:
2022
Jazyk:
eng
Abstrakt: 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.
Klíčová slova:
Bayesian networks; Decomposable Entropy; DempsterShafer belief functions Číslo projektu: GA19-04579S (CEP), GA19-06569S (CEP) Poskytovatel projektu: GA ČR, GA ČR Zdrojový dokument: Proceedings of the 12th Workshop on Uncertainty Processing, ISBN 978-80-7378-460-7