bibtype C - Conference Paper (international conference)
ARLID 0600834
utime 20250331111329.6
mtime 20241113235959.9
title (primary) (eng) On cardinalities of different degrees of Belief functions conjunctive conflictness
specification
page_count 12 s.
media_type E
serial
ARLID cav_un_epca*0600833
ISBN 978-80-905688-0-8
title Proceedings of the 24th Czech-Japan Seminar on Data Analysis and Decision Making
page_num 14-25
publisher
place Praha
name ÚTIA AV ČR
year 2024
keyword belief function
keyword conflict
keyword degree of conflict
author (primary)
ARLID cav_un_auth*0100740
name1 Daniel
name2 Milan
institution UIVT-O
full_dept (cz) Oddělení složitých systémů
full_dept (eng) Department of Complex Systems
fullinstit Ústav informatiky 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.
source
url https://cjs.utia.cas.cz/2024/proceedings.pdf#section.0.2
source
url https://library.utia.cas.cz/separaty/2024/MTR/kratochvil-0600834.pdf
cas_special
abstract (eng) This paper examines mutual conflict behavior between belief function structures across different discernment frame sizes (\(\Omega\)). Through experiments on \(\Omega_2\) to \(\Omega_6\), we observe that as frame size increases, non-conflicting pairs and higher-order hidden conflicts become exceedingly relatively rare despite the exponential growth of cardinalities of their classes. The super-exponential growth of possible belief structures complicates exhaustive analysis, leading us to employ random sampling. Our findings reveal that the cardinality of a class of first-degree hidden conflicts (HC\(_1\)) grows faster than non-conflicts as frame size increases, highlighting the challenges and implications of applying belief function theory in complex decision-making scenarios.
action
ARLID cav_un_auth*0476414
name Czech-Japan Seminar on Data Analysis and Decision Making 2024 /24./
dates 20240909
mrcbC20-s 20240912
place Telč
country CZ
RIV BB
FORD0 10000
FORD1 10100
FORD2 10102
reportyear 2025
num_of_auth 2
mrcbC47 UIVT-O 10000 10200 10201
presentation_type PR
inst_support RVO:67985556
inst_support RVO:67985807
permalink https://hdl.handle.net/11104/0358254
confidential S
arlyear 2024
mrcbU02 C
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU56 pdf
mrcbU63 cav_un_epca*0600833 Proceedings of the 24th Czech-Japan Seminar on Data Analysis and Decision Making ÚTIA AV ČR 2024 Praha 14 25 978-80-905688-0-8