bibtype J - Journal Article
ARLID 0573803
utime 20240402214200.6
mtime 20230724235959.9
SCOPUS 85165544597
WOS 001058204600001
DOI 10.1016/j.ijar.2023.108984
title (primary) (eng) Computing the decomposable entropy of belief-function graphical models
specification
page_count 21 s.
media_type P
serial
ARLID cav_un_epca*0256774
ISSN 0888-613X
title International Journal of Approximate Reasoning
volume_id 161
publisher
name Elsevier
keyword Dempster-Shafer theory of belief functions
keyword Decomposable entropy
keyword Belief-function directed graphical models
keyword Belief-function undirected graphical models
author (primary)
ARLID cav_un_auth*0101118
name1 Jiroušek
name2 Radim
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept (eng) Department of Decision Making Theory
department (cz) MTR
department (eng) MTR
full_dept Department of Decision Making Theory
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0216188
name1 Kratochvíl
name2 Václav
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept Department of Decision Making Theory
department (cz) MTR
department MTR
full_dept Department of Decision Making Theory
country CZ
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0275452
name1 Shenoy
name2 P. P.
country US
source
url http://library.utia.cas.cz/separaty/2023/MTR/jirousek-0573803.pdf
source
url https://www.sciencedirect.com/science/article/pii/S0888613X23001159?via%3Dihub
cas_special
project
project_id GA21-07494S
agency GA ČR
country CZ
ARLID cav_un_auth*0430801
abstract (eng) In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief functions called decomposable entropy (d-entropy). This paper provides an algorithm for computing the d-entropy of directed graphical D-S belief function models. We illustrate the algorithm using Almond's Captain's Problem example. For belief function undirected graphical models, assuming that the set of belief functions in the model is non-informative, the belief functions are distinct. We illustrate this using Haenni-Lehmann's Communication Network problem. As the joint belief function for this model is quasi-consonant, it follows from a property of d-entropy that the d-entropy of this model is zero, and no algorithm is required. For a class of undirected graphical models, we provide an algorithm for computing the d-entropy of such models. Finally, the d-entropy coincides with Shannon's entropy for the probability mass function of a single random variable and for a large multi-dimensional probability distribution expressed as a directed acyclic graph model called a Bayesian network. We illustrate this using Lauritzen-Spiegelhalter's Chest Clinic example represented as a belief-function directed graphical model.
action
ARLID cav_un_auth*0452419
name The 12th Workshop on Uncertainty Processing
dates 20220601
mrcbC20-s 20220604
place Kutná Hora
country CZ
result_subspec WOS
RIV BA
FORD0 10000
FORD1 10100
FORD2 10102
reportyear 2024
num_of_auth 3
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0344420
confidential S
article_num 108984
mrcbC86 Article Computer Science Artificial Intelligence
mrcbC91 A
mrcbT16-e COMPUTERSCIENCE.ARTIFICIALINTELLIGENCE
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mrcbT16-s 0.877
mrcbT16-y 47.31
mrcbT16-x 3.74
mrcbT16-3 1655
mrcbT16-4 Q1
mrcbT16-5 2.600
mrcbT16-6 155
mrcbT16-7 Q2
mrcbT16-C 57.6
mrcbT16-D Q3
mrcbT16-E Q2
mrcbT16-M 1.02
mrcbT16-N Q2
mrcbT16-P 57.6
arlyear 2023
mrcbU14 85165544597 SCOPUS
mrcbU24 PUBMED
mrcbU34 001058204600001 WOS
mrcbU63 cav_un_epca*0256774 International Journal of Approximate Reasoning 161 1 2023 0888-613X 1873-4731 Elsevier