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This paper presents an approach for developing the explanation capabilities of rule-based expert systems managing imprecise and uncertain knowledge. The treatment of uncertainty takes place in the framework of possibility theory where the…

Artificial Intelligence · Computer Science 2013-04-08 Henri Farrency , Henri Prade

Recently, it has been emphasized that the possibility theory framework allows us to distinguish between i) what is possible because it is not ruled out by the available knowledge, and ii) what is possible for sure. This distinction may be…

Artificial Intelligence · Computer Science 2013-01-07 Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade

Communicating forecast uncertainty effectively is a persistent challenge in predictive endeavours such as weather forecasting. This paper explores the application of possibility theory as a complementary approach to traditional probability…

Applications · Statistics 2024-10-30 John R. Lawson

The general use of subjective probabilities to model belief has been justified using many axiomatic schemes. For example, ?consistent betting behavior' arguments are well-known. To those not already convinced of the unique fitness and…

Artificial Intelligence · Computer Science 2013-03-25 Paul Snow

Given a universe of discourse X-a domain of possible outcomes-an experiment may consist of selecting one of its elements, subject to the operation of chance, or of observing the elements, subject to imprecision. A priori uncertainty about…

Artificial Intelligence · Computer Science 2013-03-26 Arthur Ramer

When we work with information from multiple sources, the formalism each employs to handle uncertainty may not be uniform. In order to be able to combine these knowledge bases of different formats, we need to first establish a common basis…

Artificial Intelligence · Computer Science 2013-02-18 Choh Man Teng

Probability theory is far from being the most general mathematical theory of uncertainty. A number of arguments point at its inability to describe second-order ('Knightian') uncertainty. In response, a wide array of theories of uncertainty…

Statistics Theory · Mathematics 2021-04-15 Fabio Cuzzolin

Theoretically as well as experimentally it is investigated how people represent their knowledge in order to make decisions or to share their knowledge with others. Experiment 1 probes into the ways how people 6ather information about the…

Artificial Intelligence · Computer Science 2013-04-15 Alf C. Zimmer

Specially customised Entropies are widely applied in measuring the degree of uncertainties existing in the frame of discernment. However, all of these entropies regard the frame as a whole that has already been determined which dose not…

Artificial Intelligence · Computer Science 2021-02-26 Yuanpeng He

The combination of argumentation and probability paves the way to new accounts of qualitative and quantitative uncertainty, thereby offering new theoretical and applicative opportunities. Due to a variety of interests, probabilistic…

Artificial Intelligence · Computer Science 2018-03-12 Regis Riveret , Pietro Baroni , Yang Gao , Guido Governatori , Antonino Rotolo , Giovanni Sartor

The reasoning with qualitative uncertainty measures involves comparative statements about events in terms of their likeliness without necessarily assigning an exact numerical value to these events. The paper is divided into two parts. In…

Logic · Mathematics 2024-03-18 Marta Bilkova , Sabine Frittella , Daniil Kozhemiachenko , Ondrej Majer

We define a generalized likelihood function based on uncertainty measures and show that maximizing such a likelihood function for different measures induces different types of classifiers. In the probabilistic framework, we obtain…

Machine Learning · Computer Science 2013-01-18 Loo-Nin Teow , Kia-Fock Loe

We develop a general operational framework that formalizes the concept of conditional uncertainty in a measure-independent fashion. Our formalism is built upon a mathematical relation which we call conditional majorization. We define…

This paper investigates the problem of finding a preference relation on a set of acts from the knowledge of an ordering on events (subsets of states of the world) describing the decision-maker (DM)s uncertainty and an ordering of…

Artificial Intelligence · Computer Science 2013-02-08 Didier Dubois , Helene Fargier , Henri Prade

Fuzziness and randomicity widespread exist in natural science, engineering, technology and social science. The purpose of this paper is to present a new logic - uncertain propositional logic which can deal with both fuzziness by taking…

Logic · Mathematics 2015-06-11 Maokang Luo , Wei He

Automated reasoning about uncertain knowledge has many applications. One difficulty when developing such systems is the lack of a completely satisfactory integration of logic and probability. We address this problem directly. Expressive…

Logic in Computer Science · Computer Science 2012-09-13 Marcus Hutter , John W. Lloyd , Kee Siong Ng , William T. B. Uther

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

The primary theme of this investigation is a decision theoretic account of conditional ought statements (e.g., "You ought to do A, if C") that rectifies glaring deficiencies in classical deontic logic. The resulting account forms a sound…

Artificial Intelligence · Computer Science 2013-03-08 Judea Pearl

Accepting a proposition means that our confidence in this proposition is strictly greater than the confidence in its negation. This paper investigates the subclass of uncertainty measures, expressing confidence, that capture the idea of…

Artificial Intelligence · Computer Science 2013-02-21 Didier Dubois , Henri Prade

In recent years, there has been an increased need for the use of active systems - systems required to act automatically based on events, or changes in the environment. Such systems span many areas, from active databases to applications that…

Artificial Intelligence · Computer Science 2012-07-09 Segev Wasserkrug , Avigdor Gal , Opher Etzion
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