Národní úložiště šedé literatury Nalezeno 25 záznamů.  1 - 10dalšíkonec  přejít na záznam: Hledání trvalo 0.00 vteřin. 
Modeling the spread of loanwords in South-East Asia using sailing navigation software and Bayesian networks
Kratochvíl, F. ; Kratochvíl, Václav ; Saad, G. ; Vomlel, Jiří
A loanword is a word permanently adopted from one language and incorporated into another language without translation. In this paper, we study loanwords in the South-East Asia Archipelago, home to a large number of languages. Our paper is inspired by the works of Hoffmann et al. (2021) Bayesian methods are applied to probabilistic modeling of family trees representing the history of language families and by Haynie et al. (2014) modeling the diffusion of a special class of loanwords, so-called Wanderw ̈orter in languages of Australia, North America, and South America. We assume that in the South-East Asia Archipelago Wanderwörter spread along specific maritime trade routes whose geographical characteristics can help unravel the history of Wanderwörter diffusion in the area. For millennia trade was conducted using sailing ships which were constrained by the monsoon system and in certain areas also by strong sea currents. Therefore rather than the geographical distances, the travel times of sailing ships should be considered as a major factor determining the intensity of contact among cultures. We use sailing navigation software to estimate travel times between different ports and show that the estimated travel times correspond well to the travel times of a Chinese map of the sea trade routes from the early seventeenth century. We model the spread of loanwords using a probabilistic graphical model - a Bayesian network. We design a novel heuristic Bayesian network structure learning algorithm that learns the structure as a union of spanning trees for graphs of all loanwords in the training dataset. We compare this algorithm with BIC optimal Bayesian networks by measuring how well these models predict the true presence/absence of a loanword. Interestingly, Bayesian networks learned by our heuristic spanning tree-based algorithm provide better results than the BIC optimal Bayesian networks.
Classes of Conflictness / Non-Conflictness of Belief Functions
Daniel, Milan ; Kratochvíl, Václav
Theoretic, descriptive and experimental analysis and description of classes of conflictness, non-conflictness and of conflict hiddeness of belief functions. Theoretic extension of theory of hidden conflicts. Idea of catalogue of belief structures.
Two Composition Operators for Belief Functions Revisited
Jiroušek, Radim ; Kratochvíl, Václav ; Shenoy, P. P.
In probability theory, compositional models are as powerful as Bayesian networks. However, the relation between belief-function graphical models and the corresponding compositional models is much more complicated due to several reasons. One of them is that there are two composition operators for belief functions. This paper deals with their main properties and presents sufficient conditions under which they yield the same results.
Computing the Decomposable Entropy of Graphical Belief Function Models
Jiroušek, Radim ; Kratochvíl, Václav ; Shenoy, P. P.
In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief functions called decomposable entropy. Here, we provide an algorithm for computing the decomposable entropy of directed graphical D-S belief function models. For undirected graphical belief function models, assuming that each belief function in the model is non-informative to the others, no algorithm is necessary. We compute the entropy of each belief function and add them together to get the decomposable entropy of the model. Finally, the decomposable entropy generalizes Shannon’s entropy not only for the probability of a single random variable but also for multinomial distributions expressed as directed acyclic graphical models called Bayesian networks.
On Experimental Part of Behavior under Ambiguity
Kratochvíl, Václav ; Jiroušek, Radim
People are risk-takers, risk-averse, or neutral. In the literature, one can find experiments illustrating the ambiguity aversion of human decision-makers. Recently, a personal coefficient of ambiguity aversion has been introduced. We have decided to measure the coefficient and its stability during the time. In this paper, we describe performed experiments and their structure to launch a discussion of possible design weaknesses or to suggest other methods of measuring it.
Preliminary Results from Experiments on the Behavior under Ambiguity
Jiroušek, Radim ; Kratochvíl, Václav
In the literature, some experiments proving that human decision-makers manifest an ambiguity aversion are described. In our knowledge, no one has studied a possibility to measure the strength of this aversion and its stability in time. The research, we have recently started to realize should find out answers to these and similar questions. The goal of this paper is to present some preliminary results to initiate a discussion that should help us to modify either the process of data collection and/or the analysis of the collected data.
A Step towards Upper-bound of Conflict of Belief Functions based on Non-conflicting Parts
Daniel, M. ; Kratochvíl, Václav
This study compares the size of conflict based on non-conflicting parts of belief functions $Conf$ with the sum of all multiples of bbms of disjoint focal elements of belief functions in question. In general, we make an effort to reach a simple upper bound function for $Conf$. (Nevertheless, the maximal value of conflict is, of course, equal to 1 for fully conflicting belief functions). We apply both theoretical research using the recent results on belief functions and also experimental computational approach here.
Proceedings of the 22nd Czech-Japan Seminar on Data Analysis and Decision Making
Inuiguchi, M. ; Jiroušek, Radim ; Kratochvíl, Václav
The history of the series of the Czech-Japan seminars started in 1999. Thus, it is now more than 20 years ago when the first Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty was held in JAIST, Hokuriku. Since that time, these seminars were held in eleven splendid places in Japan, offering the Czech participants possibility to discover different parts of the Japanese islands. In reciprocity, it was the goal of the Czech partners organizing the past ten seminars to show the beauty of Czechia to Japanese colleagues, who, during the long Japan–Czech cooperation, became our close friends. This is also why the seminar has never visited one place two times.
On attempts to characterize facet-defining inequalities of the cone of exact games
Studený, Milan ; Kroupa, Tomáš ; Kratochvíl, Václav
The sets of balanced, totally balanced, exact and supermodular games play an important role in cooperative game theory. These sets of games are known to be polyhedral cones. The (unique) non-redundant description of these cones by means of the so-called facet-defining inequalities is known in cases of balanced games and supermodular games, respectively. The facet description of the cones of exact games and totally balanced games are not known and we present conjectures about what are the facet-defining inequalities for these cones. We introduce the concept of an irreducible min-balanced set system and conjecture that the facet-defining inequalities for the cone of totally balanced games correspond to these set systems. The conjecture concerning exact games is that the facet-defining inequalities for this cone are those which correspond to irreducible min-balanced systems on strict subsets of the set of players and their conjugate inequalities. A consequence of the validity of the conjectures would be a novel result saying that a game m is exact if and only if m and its reflection are totally balanced.
Comparison of Shenoy’s Expectation Operator with Probabilistic Transforms and Perez’ Barycenter
Jiroušek, R. ; Kratochvíl, Václav
Shenoy’s paper published in this Proceedings of WUPES 2018 introduces an operator that gives instructions how to compute an expected value in the Dempster-Shafer theory of evidence. Up to now, there was no direct way to get the expected value of a utility function in D-S theory. If eeded, one had to find a probability mass function corresponding to the considered belief function, and then - using this probability mass function - to compute the classical probabilistic expectation. In this paper, we take four different approaches to defining probabilistic representatives of a belief function and compare which one yields to the best approximations of Shenoy’s expected values of various utility functions. The achieved results support our conjecture that there does not exist a probabilistic representative of a belief function that would yield the same expectations as the Shenoy’s new operator.

Národní úložiště šedé literatury : Nalezeno 25 záznamů.   1 - 10dalšíkonec  přejít na záznam:
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2 Kratochvíl, Viktor
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