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Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapted so as to consider non-monotonicity, with only a limited…

Artificial Intelligence · Computer Science 2023-11-15 Lucas Rizzo , Luca Longo

Prevalent semantic speech tokenizers, designed to capture linguistic content, are surprisingly fragile. We find they are not robust to meaning-irrelevant acoustic perturbations; even at high Signal-to-Noise Ratios (SNRs) where speech is…

Computation and Language · Computer Science 2026-04-15 Yuhan Song , Linhao Zhang , Chuhan Wu , Aiwei Liu , Wei Jia , Houfeng Wang , Xiao Zhou

It is outlined the possibility to extend the quantum formalism in relation to the requirements of the general systems theory. It can be done by using a quantum semantics arising from the deep logical structure of quantum theory. It is so…

General Physics · Physics 2010-04-26 Ignazio Licata

Abstract Dialectical Frameworks (ADFs) are argumentation frameworks where each node is associated with an acceptance condition. This allows us to model different types of dependencies as supports and attacks. Previous studies provided a…

Artificial Intelligence · Computer Science 2019-07-24 João Alcântara , Samy Sá , Juan Acosta-Guadarrama

We prove a theorem stating that any semantics can be encoded as a compositional semantics, which means that, essentially, the standard definition of compositionality is formally vacuous. We then show that when compositional semantics is…

cmp-lg · Computer Science 2008-02-03 Wlodek Zadrozny

The language of epistemic specifications and epistemic logic programs extends disjunctive logic programs under the stable model semantics with modal constructs called subjective literals. Using subjective literals, it is possible to check…

Artificial Intelligence · Computer Science 2021-10-06 Jorge Fandinno , Wolfgang Faber , Michael Gelfond

This paper studies the stable model semantics of logic programs with (abstract) constraint atoms and their properties. We introduce a succinct abstract representation of these constraint atoms in which a constraint atom is represented…

Artificial Intelligence · Computer Science 2009-05-01 Yi-Dong Shen , Jia-Huai You , Li-Yan Yuan

Approaches based on computing with words find good applicability in decision making systems. Predominantly finding their basis in type-1 fuzzy sets, computing with words approaches employ type-1 fuzzy sets as semantics of the linguistic…

Artificial Intelligence · Computer Science 2020-02-28 Taniya Seth , Pranab K. Muhuri

Since its establishment, propositional dynamic logic (PDL) has been a subject of intensive academic research and frequent use in the industry. We have studied the complexity of some PDL problems and in this paper, we show results for some…

Logic in Computer Science · Computer Science 2024-01-23 Mohammad Javad Hosseinpour , Farzad Didehvar

Characterizations of semi-stable and stage extensions in terms of 2-valued logical models are presented. To this end, the so-called GL-supported and GL-stage models are defined. These two classes of logical models are logic programming…

Logic in Computer Science · Computer Science 2016-03-01 Mauricio Osorio , Juan Carlos Nieves

In this paper, we present the interval neutrosophic logics which generalizes the fuzzy logic, paraconsistent logic, intuitionistic fuzzy logic and many other non-classical and non-standard logics. We will give the formal definition of…

Logic in Computer Science · Computer Science 2007-05-23 Haibin Wang , Florentin Smarandache , Yanqing Zhang , Rajshekhar Sunderraman

Dialectical frameworks are a unifying model of formal argumentation, where argumentative relations between arguments are represented by assigning acceptance conditions to atomic arguments. Their generality allow them to cover a number of…

Artificial Intelligence · Computer Science 2024-07-03 Jesse Heyninck , Matthias Knorr , João Leite

The fuzzy modality `probably` is interpreted over probabilistic type spaces by taking expected truth values. The arising probabilistic fuzzy description logic is invariant under probabilistic bisimilarity; more informatively, it is…

Logic in Computer Science · Computer Science 2019-06-05 Paul Wild , Lutz Schröder , Dirk Pattinson , Barbara König

The Smodels system implements the stable model semantics for normal logic programs. It handles a subclass of programs which contain no function symbols and are domain-restricted but supports extensions including built-in functions as well…

Artificial Intelligence · Computer Science 2007-05-23 Ilkka Niemela , Patrik Simons , Tommi Syrjanen

A logic programming paradigm which expresses solutions to problems as stable models has recently been promoted as a declarative approach to solving various combinatorial and search problems, including planning problems. In this paradigm,…

Artificial Intelligence · Computer Science 2007-05-23 Maurice Bruynooghe

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

We define an extension of predicate logic, called Binding Logic, where variables can be bound in terms and in propositions. We introduce a notion of model for this logic and prove a soundness and completeness theorem for it. This theorem is…

Logic in Computer Science · Computer Science 2023-05-26 Gilles Dowek , Thérèse Hardin , Claude Kirchner

In this paper we present, by way of case studies, a proof of concept, based on a prototype working on a automotive data set, aimed at showing the potential usefulness of using formulas of {\L}ukasiewicz propositional logic to query…

Logic in Computer Science · Computer Science 2015-12-04 Stefano Aguzzoli , Pietro Codara , Tommaso Flaminio , Brunella Gerla , Diego Valota

Artificial Intelligence models are becoming increasingly more powerful and accurate, supporting or even replacing humans' decision making. But with increased power and accuracy also comes higher complexity, making it hard for users to…

Artificial Intelligence · Computer Science 2019-07-10 Vivian S. Silva , André Freitas , Siegfried Handschuh

The relationship between communicated language and intended meaning is often probabilistic and sensitive to context. Numerous strategies attempt to estimate such a mapping, often leveraging recursive Bayesian models of communication. In…

Computation and Language · Computer Science 2023-05-03 Benjamin Lipkin , Lionel Wong , Gabriel Grand , Joshua B Tenenbaum