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Národní úložiště šedé literatury Nalezeno 3 záznamů.  Hledání trvalo 0.01 vteřin. 
Theory of SSB Representation of Preferences Revised
 Pištěk, Miroslav
A continuous skew-symmetric bilinear (SSB) representation of preferences has recently been proposed in a topological vector space, assuming a weaker notion of convexity of preferences than in the classical (algebraic) case. Equipping a linear vector space with the so-called inductive linear topology, we derive the algebraic SSB representation on a topological basis, thus weakening\nthe convexity assumption. Such a unifying approach to SSB representation permits also to fully discuss the relationship of topological and algebraic axioms of continuity, and leads to a stronger existence result for a maximal element. By applying this theory to probability measures we show the existence of a maximal preferred measure for an infinite set of pure outcomes, thus generalizing all available existence theorems in this context.
Úplný záznam
Some Results on Set-Valued Possibilistic Distributions
 Kramosil, Ivan
When proposing and processing uncertainty decision making algorithms of various kinds and purposes we meet more and more often probability distributions ascribing to random events non-numerical uncertainty degrees. 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. For the case of non-numerical uncertainty degrees at least the two criteria may be considered. First systems with rather complicated, but sophisticated and nontrivially formally analyzable uncertainty degrees. E.g., uncertainties supported by some algebras or partially ordered structures. Contrary, we may consider more easy non-numerical, but on the intuitive level interpretable relations. Well-known examples of such structures are set-valued possibilistic measures. Some perhaps interesting particular results in this direction will be introduced and analyzed in the contribution.
Úplný záznam
Definition and Approximation of Probabilistic Measures by Boolean-Valued Possibilistic Measures
 Kramosil, Ivan
Úplný záznam

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