About twenty-five naughty entropies in belief function theory: Do they measure informativeness?
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00635531" target="_blank" >RIV/67985556:_____/25:00635531 - isvavai.cz</a>
Alternative codes found
RIV/61384399:31160/25:00061251
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0888613X25000957?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0888613X25000957?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijar.2025.109454" target="_blank" >10.1016/j.ijar.2025.109454</a>
Alternative languages
Result language
angličtina
Original language name
About twenty-five naughty entropies in belief function theory: Do they measure informativeness?
Original language description
This paper addresses the long-standing challenge of identifying belief function entropies that can effectively guide model learning within the Dempster-Shafer theory of evidence. Building on the analogy with classical probabilistic approaches, we examine 25 entropy functions documented in the literature and evaluate their potential to define mutual information in the belief function framework. As conceptualized in probability theory, mutual information requires strictly subadditive entropies, which are inversely related to the informativeness of belief functions. After extensive analysis, we have found that none of the studied entropy functions fully satisfy these criteria. Nevertheless, certain entropy functions exhibit properties that may make them useful for heuristic model learning algorithms. This paper provides a detailed comparative study of these functions, explores alternative approaches using divergence-based measures, and offers insights into the design of information-theoretic tools for belief function models.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Approximate Reasoning
ISSN
0888-613X
e-ISSN
1873-4731
Volume of the periodical
184
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
109454
UT code for WoS article
001485002800001
EID of the result in the Scopus database
2-s2.0-105003665803