English
Related papers

Related papers: Probabilistic Acceptance

200 papers

In this note, we give an alternate proof of the multinomial theorem using a probabilistic approach. Although the multinomial theorem is basically a combinatorial result, our proof may be simpler for a student familiar with only basic…

General Mathematics · Mathematics 2019-07-25 K. K. Kataria

We examine the issue of stability of probability in reasoning about complex systems with uncertainty in structure. Normally, propositions are viewed as probability functions on an abstract random graph where it is implicitly assumed that…

Artificial Intelligence · Computer Science 2017-12-14 Subhash Kak

The ideas of aleatoric and epistemic uncertainty are widely used to reason about the probabilistic predictions of machine-learning models. We identify incoherence in existing discussions of these ideas and suggest this stems from the…

Machine Learning · Computer Science 2025-08-19 Freddie Bickford Smith , Jannik Kossen , Eleanor Trollope , Mark van der Wilk , Adam Foster , Tom Rainforth

The theory of probability and the quantum theory, the one mathematical and the other physical, are related in that each admits a number of very different interpretations. It has been proposed that the conceptual problems of the quantum…

Quantum Physics · Physics 2021-08-29 Louis Marchildon

Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabilistic argumentation frameworks provide modelling tools to…

Artificial Intelligence · Computer Science 2023-04-18 Pietro Totis , Angelika Kimmig , Luc De Raedt

Possibility theory offers a framework where both Lehmann's "preferential inference" and the more productive (but less cautious) "rational closure inference" can be represented. However, there are situations where the second inference does…

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

Likelihood-based methods of statistical inference provide a useful general methodology that is appealing, as a straightforward asymptotic theory can be applied for their implementation. It is important to assess the relationships between…

Statistics Theory · Mathematics 2015-03-20 Thomas J. DiCiccio , Todd A. Kuffner , G. Alastair Young , Russell Zaretzki

Classical probability theory supports probability measures, assigning a fixed positive real value to each event, these measures are far from satisfactory in formulating real-life occurrences. The main innovation of this paper is the…

Probability · Mathematics 2009-02-09 Yehuda Izhakian , Zur Izhakian

General acceptance of a mathematical proposition $P$ as a theorem requires convincing evidence that a proof of $P$ exists. But what constitutes "convincing evidence?" I will argue that, given the types of evidence that are currently…

History and Overview · Mathematics 2017-04-11 Jeffrey C. Jackson

We give a probabilistic analysis of inductive knowledge and belief and explore its predictions concerning knowledge about the future, about laws of nature, and about the values of inexactly measured quantities. The analysis combines a…

Logic in Computer Science · Computer Science 2021-06-23 Jeremy Goodman , Bernhard Salow

In this paper we provide a first analysis of the research questions that arise when dealing with the problem of communicating pieces of formal argumentation through natural language interfaces. It is a generally held opinion that formal…

Artificial Intelligence · Computer Science 2017-06-14 Federico Cerutti , Alice Toniolo , Timothy J. Norman

Supervised machine learning models boast remarkable predictive capabilities. But can you trust your model? Will it work in deployment? What else can it tell you about the world? We want models to be not only good, but interpretable. And yet…

Machine Learning · Computer Science 2017-03-07 Zachary C. Lipton

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

Plausible reasoning concerns situations whose inherent lack of precision is not quantified; that is, there are no degrees or levels of precision, and hence no use of numbers like probabilities. A hopefully comprehensive set of principles…

Artificial Intelligence · Computer Science 2017-04-05 David Billington

Inspired by the theory of desirable gambles that is used to model uncertainty in the field of imprecise probabilities, I present a theory of desirable things. Its aim is to model a subject's beliefs about which things are desirable. What…

Artificial Intelligence · Computer Science 2023-05-12 Jasper De Bock

The analysis of decision making under uncertainty is closely related to the analysis of probabilistic inference. Indeed, much of the research into efficient methods for probabilistic inference in expert systems has been motivated by the…

Artificial Intelligence · Computer Science 2013-03-25 Ross D. Shachter , Mark Alan Peot

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

Classical countably additive real-valued probabilities come at a philosophical cost: in many infinite situations, they assign the same probability value -- namely, zero -- to cases that are impossible as well as to cases that are possible.…

Probability · Mathematics 2022-08-29 Alexander R. Pruss

We provide a formal, simple and intuitive theory of rational decision making including sequential decisions that affect the environment. The theory has a geometric flavor, which makes the arguments easy to visualize and understand. Our…

Machine Learning · Computer Science 2012-02-10 Peter Sunehag , Marcus Hutter

In this paper we discuss contrastive explanations for formal argumentation - the question why a certain argument (the fact) can be accepted, whilst another argument (the foil) cannot be accepted under various extension-based semantics. The…

Artificial Intelligence · Computer Science 2022-01-26 AnneMarie Borg , Floris Bex