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Related papers: Inference with Possibilistic Evidence

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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

This paper addresses the problem of merging uncertain information in the framework of possibilistic logic. It presents several syntactic combination rules to merge possibilistic knowledge bases, provided by different sources, into a new…

Artificial Intelligence · Computer Science 2013-02-01 Salem Benferhat , Claudio Sossai

This paper suggests a new interpretation of the Dempster-Shafer theory in terms of probabilistic interpretation of plausibility. A new rule of combination of independent evidence is shown and its preservation of interpretation is…

Artificial Intelligence · Computer Science 2017-04-07 Mieczysław Kłopotek

Possibilistic logic, an extension of first-order logic, deals with uncertainty that can be estimated in terms of possibility and necessity measures. Syntactically, this means that a first-order formula is equipped with a possibility degree…

Artificial Intelligence · Computer Science 2013-02-28 Bernhard Hollunder

Besides the classical motivation of fusing evidence from multiple sources, modern inferential procedures based on randomization, resampling, and data splitting often introduce analyst-generated multiplicity, where aggregating outputs across…

Methodology · Statistics 2026-05-29 Leonardo Cella

This paper presents a plausible reasoning system to illustrate some broad issues in knowledge representation: dualities between different reasoning forms, the difficulty of unifying complementary reasoning styles, and the approximate nature…

Artificial Intelligence · Computer Science 2013-03-26 Wray L. Buntine

This paper addresses fundamental issues on the nature of the concepts and structures of fuzzy logic, focusing, in particular, on the conceptual and functional differences that exist between probabilistic and possibilistic approaches. A…

Artificial Intelligence · Computer Science 2013-04-05 Enrique H. Ruspini

Humans currently use arguments for explaining choices which are already made, or for evaluating potential choices. Each potential choice has usually pros and cons of various strengths. In spite of the usefulness of arguments in a decision…

Artificial Intelligence · Computer Science 2012-07-19 Leila Amgoud , Henri Prade

This paper is motivated by the questions of how to give the concept of probability an adequate real-world meaning, and how to explain a certain type of phenomenon that can be found, for instance, in Ellsberg's paradox. It attempts to answer…

Other Statistics · Statistics 2022-03-25 Russell J. Bowater

An agent often has a number of hypotheses, and must choose among them based on observations, or outcomes of experiments. Each of these observations can be viewed as providing evidence for or against various hypotheses. All the attempts to…

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

Possibilistic logic bases and possibilistic graphs are two different frameworks of interest for representing knowledge. The former stratifies the pieces of knowledge (expressed by logical formulas) according to their level of certainty,…

Artificial Intelligence · Computer Science 2013-01-30 Salem Benferhat , Didier Dubois , Laurent Garcia , Henri Prade

An agent often has a number of hypotheses, and must choose among them based on observations, or outcomes of experiments. Each of these observations can be viewed as providing evidence for or against various hypotheses. All the attempts to…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern , Riccardo Pucella

We develop a logical framework for reasoning about knowledge and evidence in which the agent may be uncertain about how to interpret their evidence. Rather than representing an evidential state as a fixed subset of the state space, our…

Logic in Computer Science · Computer Science 2019-07-23 Adam Bjorndahl , Aybüke Özgün

The process of doing Science in condition of uncertainty is illustrated with a toy experiment in which the inferential and the forecasting aspects are both present. The fundamental aspects of probabilistic reasoning, also relevant in real…

History and Overview · Mathematics 2018-02-07 Giulio D'Agostini

A scientific reasoning system makes decisions using objective evidence in the form of independent experimental trials, propositional axioms, and constraints on the probabilities of events. As a first step towards this goal, we propose a…

Artificial Intelligence · Computer Science 2013-04-05 David Sher

This paper considers the notion of possible events which are insignificant in probabilistic analysis (i.e. events that have zero probability). The paper discusses the method of modal logic based on "possible worlds" and discusses a…

Other Statistics · Statistics 2022-11-08 Ben O'Neill

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 intuitive notion of evidence has both semantic and syntactic features. In this paper, we develop an {\em evidence logic} for epistemic agents faced with possibly contradictory evidence from different sources. The logic is based on a…

Logic · Mathematics 2013-07-05 Johan van Benthem , David Fernández-Duque , Eric Pacuit

The aim of this work is to provide a unified framework for ordinal representations of uncertainty lying at the crosswords between possibility and probability theories. Such confidence relations between events are commonly found in monotonic…

Artificial Intelligence · Computer Science 2012-08-07 Didier Dubois , Helene Fargier

Abstract argumentation offers an appealing way of representing and evaluating arguments and counterarguments. This approach can be enhanced by a probability assignment to each argument. There are various interpretations that can be ascribed…

Artificial Intelligence · Computer Science 2014-05-15 Anthony Hunter , Matthias Thimm
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