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Proceedings of the 11th Workshop on Uncertainty Processing
Kratochvíl, Václav ; Vejnarová, Jiřina
The Workshop on Uncertainty Processing, better known under its abbreviation WUPES, celebrates its 30-year anniversary this year. In 1988, when the first Workshop took place, Czechoslovakia was still a communist country and a part of the Soviet bloc. Since then, many things have changed. For example, Czechoslovakia no longer exists as a country (because in 1993 it was peacefully split into two independent countries - Czechia and Slovakia). From this perspective, it is hard to believe that we have several participants who have attended most workshops in the the thirty-year history of WUPES. As of now, the Program Committee has accepted, based on the extended abstracts, 21 papers to be presented at the Workshop, and 19 out of them are to be published in the present Conference Proceedings. These papers cover diverse topics, such as information processing, decision making, and data analysis, but what is common to most of them is that they are related to uncertainty calculus - Bayesian Networks, Dempster-Shafer Theory, Belief Functions, Probabilistic Logic, Game Theory, etc.
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On Weakness of Evidential Networks
Vejnarová, Jiřina
In evidence theory several counterparts of Bayesian networks based on different paradigms have been proposed. We will present, through simple examples, problems appearing in two kinds of these models caused either by the conditional independence concept (or its misinterpretation) or by the use of a conditioning rule. The latter kind of problems can be avoided if undirected models are used instead.
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On Three Conditioning Rules in Evidence Theory
Vejnarová, Jiřina
In evidence theory various rules were proposed to define conditional beliefs and/or plausibilities (or basic assignments). However, there exist no generally accepted criteria along which these rules can be compared. In this paper we concentrate to three of them (Dempster's conditioning rule, focusing and the approach based on lower and upper envelopes of sets of conditional probabilities) to study their mutual relationship. A new conditional rule for variables is presented afterwards and its correctness is proven.
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Kompozicionální modely domněnkvých funkcí
Jiroušek, Radim ; Vejnarová, Jiřina ; Daniel, Milan
After it has been successfully done in probability and possibility theories, the paper is the first attempt to introduce the operator of composition also for belief functions. We prove that the proposed definition preserves all the necessary properties of the operator enabling us to define compositional models as an efficient tool for multidimensional models representation.
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Možnosti Iterativní proporcionální fitující procedůry
Vejnarová, Jiřina
Iterative Proportional Fitting Procedure (parameterized by a continuous t-norm) for computation of multidimensional possibility distributions from its marginals designed in 2003, is discussed in more details. Special attention is paid to its application to possibilistic marginal problem.
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