bibtype |
K -
Conference Paper (Czech conference)
|
ARLID |
0558135 |
utime |
20230316105120.0 |
mtime |
20220613235959.9 |
title
(primary) (eng) |
Computing the Decomposable Entropy of Graphical Belief Function Models |
specification |
page_count |
12 s. |
media_type |
P |
|
serial |
ARLID |
cav_un_epca*0558134 |
ISBN |
978-80-7378-460-7 |
title
|
Proceedings of the 12th Workshop on Uncertainty Processing |
page_num |
111-122 |
publisher |
place |
Prague |
name |
MatfyzPress |
year |
2022 |
|
editor |
name1 |
Studený |
name2 |
Milan |
|
editor |
|
editor |
name1 |
Coletti |
name2 |
Giulianella |
|
editor |
name1 |
Kleiter |
name2 |
Gernot D. |
|
editor |
name1 |
Shenoy |
name2 |
Prakash P. |
|
|
keyword |
Decomposable Entropy |
keyword |
DempsterShafer belief functions |
keyword |
Bayesian networks |
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 |
|
cas_special |
project |
project_id |
GA19-04579S |
agency |
GA ČR |
country |
CZ |
ARLID |
cav_un_auth*0380558 |
|
project |
project_id |
GA19-06569S |
agency |
GA ČR |
country |
CZ |
ARLID |
cav_un_auth*0380559 |
|
abstract
(eng) |
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. |
action |
ARLID |
cav_un_auth*0431432 |
name |
WUPES 2022: 12th Workshop on Uncertainty Processing |
dates |
20220601 |
mrcbC20-s |
20220604 |
place |
Kutná Hora |
country |
CZ |
|
RIV |
BA |
FORD0 |
10000 |
FORD1 |
10100 |
FORD2 |
10102 |
reportyear |
2023 |
num_of_auth |
3 |
presentation_type |
PR |
inst_support |
RVO:67985556 |
permalink |
http://hdl.handle.net/11104/0332321 |
confidential |
S |
arlyear |
2022 |
mrcbU14 |
SCOPUS |
mrcbU24 |
PUBMED |
mrcbU34 |
WOS |
mrcbU63 |
cav_un_epca*0558134 Proceedings of the 12th Workshop on Uncertainty Processing MatfyzPress 2022 Prague 111 122 978-80-7378-460-7 |
mrcbU67 |
Studený Milan 340 |
mrcbU67 |
Ay Nihat 340 |
mrcbU67 |
Coletti Giulianella 340 |
mrcbU67 |
Kleiter Gernot D. 340 |
mrcbU67 |
Shenoy Prakash P. 340 |
|