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Classical evaluations of configurations of intertwined quantum contexts induce relations, such as true-implies-false, true-implies-true, but also nonseparability among the input and output terminals. When combined, these exploitable…

Quantum Physics · Physics 2020-05-14 Karl Svozil

A distinction is sometimes made between "statistical" and "subjective" probabilities. This is based on a distinction between "unique" events and "repeatable" events. We argue that this distinction is untenable, since all events are "unique"…

Artificial Intelligence · Computer Science 2013-04-11 Henry E. Kyburg

A wide variety of model explanation approaches have been proposed in recent years, all guided by very different rationales and heuristics. In this paper, we take a new route and cast interpretability as a statistical inference problem. We…

Machine Learning · Computer Science 2024-01-01 Hugo Henri Joseph Senetaire , Damien Garreau , Jes Frellsen , Pierre-Alexandre Mattei

We investigate abstract model theoretic properties which holds for models in which a truth or satisfaction predicate for a sublanguage of the signature is definable. We analyse in which cases those properties in fact ensure the definability…

Logic · Mathematics 2023-04-04 Mateusz Łełyk , Bartosz Wcisło

Current natural language systems designed for multi-step claim validation typically operate in two phases: retrieve a set of relevant premise statements using heuristics (planning), then generate novel conclusions from those statements…

Computation and Language · Computer Science 2023-07-07 Zayne Sprague , Kaj Bostrom , Swarat Chaudhuri , Greg Durrett

Canonical inference rules and canonical systems are defined in the framework of non-strict single-conclusion sequent systems, in which the succeedents of sequents can be empty. Important properties of this framework are investigated, and a…

Logic in Computer Science · Computer Science 2015-07-01 Arnon Avron , Ori Lahav

Induction is the process by which we obtain predictive laws or theories or models of the world. We consider the structural aspect of induction. We answer the question as to whether we can find a finite and minmalistic set of operations on…

Artificial Intelligence · Computer Science 2011-07-05 Adrian Silvescu , Vasant Honavar

The use of exponentials in linear logic greatly enhances its expressive power. In this paper we focus on nonassociative noncommutative multiplicative linear logic, and systematically explore modal axioms K, T, and 4 as well as the…

Logic in Computer Science · Computer Science 2023-06-23 Eben Blaisdell

In this paper, we axiomatize the negatable consequences in dependence and independence logic by extending the systems of natural deduction of the logics given in (Kontinen and Vaananen 2013) and (Hannula 2015). We prove a characterization…

Logic · Mathematics 2018-12-19 Fan Yang

Ordinary and transfinite recursion and induction and ZF set theory are used to construct from a fully interpreted object language and from an extra formula a new language. It is fully interpreted under a suitably defined interpretation.…

Logic · Mathematics 2017-12-15 Seppo Heikkilä

While natural languages are compositional, how state-of-the-art neural models achieve compositionality is still unclear. We propose a deep network, which not only achieves competitive accuracy for text classification, but also exhibits…

Computation and Language · Computer Science 2017-07-07 Hongyu Guo

The aim of the present paper is to show that the concept of intuitionistic logic based on a Heyting algebra can be generalized in such a way that it is formalized by means of a bounded poset. In this case it is not assumed that the poset is…

Logic · Mathematics 2023-08-23 Ivan Chajda , Helmut Länger

When does society eventually learn the truth, or take the correct action, via observational learning? In a general model of sequential learning over social networks, we identify a simple condition for learning dubbed excludability.…

Theoretical Economics · Economics 2024-04-05 Navin Kartik , SangMok Lee , Tianhao Liu , Daniel Rappoport

Ontologies formalise how the concepts from a given domain are interrelated. Despite their clear potential as a backbone for explainable AI, existing ontologies tend to be highly incomplete, which acts as a significant barrier to their more…

Artificial Intelligence · Computer Science 2021-05-12 Steven Schockaert , Yazmín Ibáñez-García , Víctor Gutiérrez-Basulto

A probabilistic propositional logic, endowed with an epistemic component for asserting (non-)compatibility of diagonizable and bounded observables, is presented and illustrated for reasoning about the random results of projective…

Logic · Mathematics 2018-03-20 A. Sernadas , J. Rasga , C. Sernadas , L. Alcácer , A. B. Henriques

Formal reasoning with non-denoting terms, esp. non-referring descriptions such as "the King of France", is still an under-investigated area. The recent exception being a series of papers e.g. by Indrzejczak, Zawidzki and K\"rbis. The…

Logic in Computer Science · Computer Science 2025-01-03 Jiří Raclavský

We extend description logics (DLs) with non-monotonic reasoning features. We start by investigating a notion of defeasible subsumption in the spirit of defeasible conditionals as studied by Kraus, Lehmann and Magidor in the propositional…

Artificial Intelligence · Computer Science 2019-04-17 Katarina Britz , Giovanni Casini , Thomas Meyer , Kody Moodley , Uli Sattler , Ivan Varzinczak

The classical propositional logic is known to be sound and complete with respect to the set semantics that interprets connectives as set operations. The paper extends propositional language by a new binary modality that corresponds to…

Logic in Computer Science · Computer Science 2007-05-23 Pavel Naumov

The categorical compositional distributional model of natural language provides a conceptually motivated procedure to compute the meaning of sentences, given grammatical structure and the meanings of its words. This approach has…

Computation and Language · Computer Science 2016-01-26 Desislava Bankova , Bob Coecke , Martha Lewis , Daniel Marsden

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