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Cathoristic logic is a multi-modal logic where negation is replaced by a novel operator allowing the expression of incompatible sentences. We present the syntax and semantics of the logic including complete proof rules, and establish a…

Logic in Computer Science · Computer Science 2014-11-27 Richard Prideaux Evans , Martin Berger

Abstraction logic is a new logic, serving as a foundation of mathematics. It combines features of both predicate logic and higher-order logic: abstraction logic can be viewed both as higher-order logic minus static types as well as…

Logic in Computer Science · Computer Science 2022-07-13 Steven Obua

Fuzzy implication functions constitute fundamental operators in fuzzy logic systems, extending classical conditionals to manage uncertainty in logical inference. Among the extensive families of these operators, generalizations of the…

Artificial Intelligence · Computer Science 2025-09-23 Raquel Fernandez-Peralta , Andrea Mesiarová-Zemánková

We consider a proper propositional quantum logic and show that it has multiple disjoint lattice models, only one of which is an orthomodular lattice (algebra) underlying Hilbert (quantum) space. We give an equivalent proof for the classical…

Quantum Physics · Physics 2016-09-19 Mladen Pavicic

One of the main challenges in the area of Neuro-Symbolic AI is to perform logical reasoning in the presence of both neural and symbolic data. This requires combining heterogeneous data sources such as knowledge graphs, neural model…

Artificial Intelligence · Computer Science 2024-03-06 Matthias Lanzinger , Stefano Sferrazza , Przemysław A. Wałęga , Georg Gottlob

In the context of general rough sets, the act of combining two things to form another is not straightforward. The situation is similar for other theories that concern uncertainty and vagueness. Such acts can be endowed with additional…

Artificial Intelligence · Computer Science 2023-09-26 A Mani

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

By the means of lower and upper fuzzy approximations we define quasiorders. Their properties are used to prove our main results. First, we characterize those pairs of fuzzy sets which form fuzzy rough sets w.r.t. a t-similarity relation…

General Mathematics · Mathematics 2023-09-11 Dávid Gégény , Sándor Radeleczki

It is shown that quantum logic is a logic in the very same way in which classical logic is a logic. Soundness and completeness of both quantum and classical logics have been proved for novel lattice models that are not orthomodular and…

Quantum Physics · Physics 2008-12-16 Mladen Pavicic , Norman D. Megill

We use princiles of fuzzy logic to develop a general model representing several processes in a system's operation characterized by a degree of vagueness and/or uncertainy. Further, we introduce three altenative measures of a fuzzy system's…

Artificial Intelligence · Computer Science 2012-12-12 Michael Gr. Voskoglou

We present a fuzzy version of description logics with concrete domains. Main features are: (i) concept constructors are based on t-norm, t-conorm, negation and implication; (ii) concrete domains are fuzzy sets; (iii) fuzzy modifiers are…

Artificial Intelligence · Computer Science 2012-07-09 Umberto Straccia

We propose a semantic representation of the standard quantum logic QL within a classical, normal modal logic, and this via a lattice-embedding of orthomodular lattices into Boolean algebras with one modal operator. Thus our classical logic…

Quantum Physics · Physics 2017-02-08 Simon Kramer

This paper mainly focuses on (1) a generalized treatment of fuzzy sets of type $n$, where $n$ is an integer larger than or equal to $1$, with an example, mathematical discussions, and real-life interpretation of the given mathematical…

Artificial Intelligence · Computer Science 2022-10-04 Anahita Jamshidnejad

Nonmonotonic logics are usually characterized by the presence of some notion of 'conditional' that fails monotonicity. Research on nonmonotonic logics is therefore largely concerned with the defeasibility of argument forms and the…

Logic in Computer Science · Computer Science 2013-10-29 Katarina Britz , Ivan Varzinczak

The aim of this article is to generalize logics of formal inconsistency ($\textbf{LFI}$s) to systems dealing with the concept of incompatibility, expressed by means of a binary connective. The basic idea is that having two incompatible…

Logic · Mathematics 2022-02-23 Marcelo Esteban Coniglio , Guilherme Vicentin de Toledo

The paper introduces fuzzy linguistic logic programming, which is a combination of fuzzy logic programming, introduced by P. Vojtas, and hedge algebras in order to facilitate the representation and reasoning on human knowledge expressed in…

Logic in Computer Science · Computer Science 2009-04-06 Van Hung Le , Fei Liu , Dinh Khang Tran

In this work we propose a formal system for fuzzy algebraic reasoning. The sequent calculus we define is based on two kinds of propositions, capturing equality and existence of terms as members of a fuzzy set. We provide a sound semantics…

Logic in Computer Science · Computer Science 2021-10-22 Davide Castelnovo , Marino Miculan

Defeasible logic is a rule-based nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts…

Artificial Intelligence · Computer Science 2009-09-29 Michael J. Maher

This paper analyses the declarative readings of logic programming. Logic programming - and negation as failure - has no unique declarative reading. One common view is that logic programming is a logic for default reasoning, a sub-formalism…

Logic in Computer Science · Computer Science 2007-05-23 Marc Denecker

Fuzzy reasoning is vital due to the frequent use of imprecise information in daily contexts. However, the ability of current large language models (LLMs) to handle such reasoning remains largely uncharted. In this paper, we introduce a new…

Artificial Intelligence · Computer Science 2024-07-04 Yiyuan Li , Shichao Sun , Pengfei Liu