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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

There are different approaches to qualitative probability, which includes subjective probability. We developed a representation of qualitative probability based on relational systems, which allows modeling uncertainty by probability…

Probability · Mathematics 2017-03-01 Mark Burgin

Grammaticality and likelihood are distinct notions in human language. Pretrained language models (LMs), which are probabilistic models of language fitted to maximize corpus likelihood, generate grammatically well-formed text and…

Computation and Language · Computer Science 2026-05-07 Yingshan Susan Wang , Linlu Qiu , Zhaofeng Wu , Roger P. Levy , Yoon Kim

By Solovay's celebrated completeness result on formal provability we know that the provability logic $\mathrm GL$ describes exactly all provable structural properties for any sound and strong enough arithmetical theory with a decidable…

Logic · Mathematics 2021-07-01 Joost J. Joosten

Inspired by its fundamental importance in quantum mechanics, we define and study the notion of entanglement for abstract physical theories, investigating its profound connection with the concept of superposition. We adopt the formalism of…

Quantum Physics · Physics 2019-10-11 Guillaume Aubrun , Ludovico Lami , Carlos Palazuelos

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

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

A semantics is given to possibilistic logic, a logic that handles weighted classical logic formulae, and where weights are interpreted as lower bounds on degrees of certainty or possibility, in the sense of Zadeh's possibility theory. The…

Artificial Intelligence · Computer Science 2013-03-26 Jerome Lang , Didier Dubois , Henri Prade

A shallow semantical embedding for public announcement logic with relativized common knowledge is presented. This embedding enables the first-time automation of this logic with off-the-shelf theorem provers for classical higher-order logic.…

Artificial Intelligence · Computer Science 2020-10-05 Sebastian Reiche , Christoph Benzmüller

The hidden variable formalism (based on the assumption of some intrinsic node parameters) turned out to be a remarkably efficient and powerful approach in describing and analyzing the topology of complex networks. Owing to one of its most…

Physics and Society · Physics 2019-08-13 Sámuel G. Balogh , Péter Pollner , Gergely Palla

Word embeddings have been found to capture a surprisingly rich amount of syntactic and semantic knowledge. However, it is not yet sufficiently well-understood how the relational knowledge that is implicitly encoded in word embeddings can be…

Artificial Intelligence · Computer Science 2017-08-22 Zied Bouraoui , Shoaib Jameel , Steven Schockaert

Do LMs infer the semantics of text from co-occurrence patterns in their training data? Merrill et al. (2022) argue that, in theory, sentence co-occurrence probabilities predicted by an optimal LM should reflect the entailment relationship…

Computation and Language · Computer Science 2024-07-18 William Merrill , Zhaofeng Wu , Norihito Naka , Yoon Kim , Tal Linzen

A theory of measurement uncertainty is presented, which, since it is based exclusively on the Bayesian approach and on the subjective concept of conditional probability, is applicable in the most general cases. The recent International…

Data Analysis, Statistics and Probability · Physics 2008-02-03 G. D'Agostini

We introduce a dual-threshold probabilistic knowing value logic for uncertain multi-agent settings. The framework captures within a single formalism both probabilistic-threshold attitudes toward propositions and high-confidence attitudes…

Logic in Computer Science · Computer Science 2026-03-27 Shanxia Wang

Let L be some extension of classical propositional logic. The non-iterated probabilistic logic over L, is the logic PL that is defined by adding non-nested probabilistic operators in the language of L. For example in PL we can express a…

Logic in Computer Science · Computer Science 2019-02-12 Ioannis Kokkinis

Metrics of model goodness-of-fit, model comparison, and model parameter estimation are the main categories of statistical problems in science. Bayesian and frequentist methods that address these questions often rely on a likelihood…

Data Analysis, Statistics and Probability · Physics 2019-06-26 Carlos A. Argüelles , Austin Schneider , Tianlu Yuan

By probabilistic logic I mean a normative theory of belief that explains how a body of evidence affects one's degree of belief in a possible hypothesis. A new axiomatization of such a theory is presented which avoids a finite additivity…

Artificial Intelligence · Computer Science 2013-04-10 Romas Aleliunas

In this article the idea of random variables over the set theoretic universe is investigated. We explore what it can mean for a random set to have a specific probability of belonging to an antecedently given class of sets.

Logic · Mathematics 2019-03-21 Hazel Brickhill , Leon Horsten

In this paper we analyze the existence of joint probabilities for the Bell-type and GHZ entangled states. We then propose the usage of nonmonotonic upper probabilities as a tool to derive consistent joint upper probabilities for the…

Quantum Physics · Physics 2010-10-18 Jose Acacio de Barros , Patrick Suppes

The idea of fully accepting statements when the evidence has rendered them probable enough faces a number of difficulties. We leave the interpretation of probability largely open, but attempt to suggest a contextual approach to full belief.…

Artificial Intelligence · Computer Science 2013-02-08 Henry E. Kyburg
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