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One important obstacle in applying Dempster-Shafer Theory (DST) is its relationship to frequencies. In particular, there exist serious difficulties in finding factorizations of belief functions from data. In probability theory…

Artificial Intelligence · Computer Science 2018-12-17 Andrzej Matuszewski , Mieczysław A. Kłopotek

This paper discusses belief revision under uncertain inputs in the framework of possibility theory. Revision can be based on two possible definitions of the conditioning operation, one based on min operator which requires a purely ordinal…

Artificial Intelligence · Computer Science 2013-02-18 Didier Dubois , Henri Prade

In this paper, we generalize the basic notions and results of Dempster-Shafer theory from predicates to formal concepts. Results include the representation of conceptual belief functions as inner measures of suitable probability functions,…

Artificial Intelligence · Computer Science 2021-05-19 Sabine Frittella , Krishna Manoorkar , Alessandra Palmigiano , Apostolos Tzimoulis , Nachoem M. Wijnberg

This paper presents two new promising rules of combination for the fusion of uncertain and potentially highly conflicting sources of evidences in the framework of the theory of belief functions in order to palliate the well-know limitations…

Artificial Intelligence · Computer Science 2007-05-23 M. C. Florea , J. Dezert , P. Valin , F. Smarandache , Anne-Laure Jousselme

We propose a method for combining probabilistic outputs of classifiers to make a single consensus class prediction when no further information about the individual classifiers is available, beyond that they have been trained for the same…

Machine Learning · Computer Science 2020-09-02 Jordan F. Masakuna , Simukai W. Utete , Steve Kroon

While explainability is a desirable characteristic of increasingly complex black-box models, modern explanation methods have been shown to be inconsistent and contradictory. The semantics of explanations is not always fully understood - to…

Artificial Intelligence · Computer Science 2024-08-09 Omer Reingold , Judy Hanwen Shen , Aditi Talati

There are several contexts of non-monotonic reasoning where a priority between rules is established whose purpose is preventing conflicts. One formalism that has been widely employed for non-monotonic reasoning is the sceptical one known as…

Artificial Intelligence · Computer Science 2012-11-26 Guido Governatori , Francesco Olivieri , Simone Scannapieco , Matteo Cristani

Evidential reasoning in expert systems has often used ad-hoc uncertainty calculi. Although it is generally accepted that probability theory provides a firm theoretical foundation, researchers have found some problems with its use as a…

Artificial Intelligence · Computer Science 2013-04-15 Robert Fung , Chee Yee Chong

Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapted so as to consider non-monotonicity, with only a limited…

Artificial Intelligence · Computer Science 2023-11-15 Lucas Rizzo , Luca Longo

When reasoning with uncertainty there are many situations where evidences are not only uncertain but their propositions may also be weakly specified in the sense that it may not be certain to which event a proposition is referring. It is…

Artificial Intelligence · Computer Science 2007-05-23 Johan Schubert

In this chapter, we present and discuss a new generalized proportional conflict redistribution rule. The Dezert-Smarandache extension of the Demster-Shafer theory has relaunched the studies on the combination rules especially for the…

Artificial Intelligence · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

In this paper we introduce a nonmonotonic framework for belief revision in which reasoning about the reliability of different pieces of information based on meta-knowledge about the information is possible, and where revision strategies can…

Artificial Intelligence · Computer Science 2007-05-23 Gerhard Brewka

We develop our interpretation of the joint belief distribution and of evidential updating that matches the following basic requirements: * there must exist an efficient method for reasoning within this framework * there must exist a clear…

Artificial Intelligence · Computer Science 2017-04-14 Mieczysław Kłopotek

In this paper, we propose to learn sources independence in order to choose the appropriate type of combination rules when aggregating their beliefs. Some combination rules are used with the assumption of their sources independence whereas…

Artificial Intelligence · Computer Science 2015-01-21 Mouna Chebbah , Mouloud Kharoune , Arnaud Martin , Boutheina Ben Yaghlane

Non-deductive reasoning systems are often {\em representation dependent}: representing the same situation in two different ways may cause such a system to return two different answers. Some have viewed this as a significant problem. For…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Daphne Koller

Current approaches to expert systems' reasoning under uncertainty fail to capture the iterative revision process characteristic of intelligent human reasoning. This paper reports on a system, called the Non-monotonic Probabilist, or NMP…

Artificial Intelligence · Computer Science 2013-04-12 Kathryn Blackmond Laskey , Marvin S. Cohen

This paper presents a general method for combining uncertain and paradoxical source of evidences for a wide class of fusion problems. From the foundations of the Dezert-Smarandache Theory (DSmT) we show how the DSm rule of combination can…

Dynamical Systems · Mathematics 2007-05-23 Jean Dezert , Florentin Smarandache

In the current versions of the Dempster-Shafer theory, the only essential restriction on the validity of the rule of combination is that the sources of evidence must be statistically independent. Under this assumption, it is permissible to…

Artificial Intelligence · Computer Science 2013-04-12 Lotfi Zadeh , Anca Ralescu

In an earlier article [J. Schubert, On nonspecific evidence, Int. J. Intell. Syst. 8(6), 711-725 (1993)] we established within Dempster-Shafer theory a criterion function called the metaconflict function. With this criterion we can…

Artificial Intelligence · Computer Science 2007-05-23 Johan Schubert

Default logic encounters some conceptual difficulties in representing common sense reasoning tasks. We argue that we should not try to formulate modular default rules that are presumed to work in all or most circumstances. We need to take…

Artificial Intelligence · Computer Science 2013-02-08 Choh Man Teng