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Several Results on Set-Valued Possibilistic Distributions

SYSNO ASEP	0444153
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Several Results on Set-Valued Possibilistic Distributions
Author(s)	Kramosil, Ivan (UIVT-O)_SAI Daniel, Milan (UIVT-O)_{RID, SAI, ORCID}
Source Title	Kybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i. - ISSN 0023-5954 Roč. 51, č. 3 (2015), s. 391-407
Number of pages	17 s.
Language	eng - English
Country	CZ - Czech Republic
Keywords	probability measures ; possibility measures ; non-numerical uncertainty degrees ; set-valued uncertainty degrees ; possibilistic uncertainty functions ; set-valued entropy functions
Subject RIV	BA - General Mathematics
R&D Projects	GAP202/10/1826 GA ČR - Czech Science Foundation (CSF)
Institutional support	UIVT-O - RVO:67985807
UT WOS	000361266300002
EID SCOPUS	84940036692
DOI	10.14736/kyb-2015-3-0391
Annotation	When proposing and processing uncertainty decision-making algorithms of various kinds and purposes, we more and more often meet probability distributions ascribing non-numerical uncertainty degrees to random events. The reason is that we have to process systems of uncertainties for which the classical conditions like sigma-additivity or linear ordering of values are too restrictive to define sufficiently closely the nature of uncertainty we would like to specify and process. In cases of non-numerical uncertainty degrees, at least the following two criteria may be considered. The first criterion should be systems with rather complicated, but sophisticated and nontrivially formally analyzable uncertainty degrees, e. g., uncertainties supported by some algebras or partially ordered structures. Contrarily, we may consider easier relations, which are non-numerical but interpretable on the intuitive level. Well-known examples of such structures are set-valued possibilistic measures. Some specific interesting results in this direction are introduced and analyzed in this contribution.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2016

Number of the records: 1