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Uncertainty in Logic Programming has been investigated during the last decades, dealing with various extensions of the classical LP paradigm and different applications. Existing proposals rely on different approaches, such as clause…

Logic in Computer Science · Computer Science 2010-07-22 Mario Rodríguez-Artalejo , Carlos A. Romero-Díaz

Uncertainty in logic programming has been widely investigated in the last decades, leading to multiple extensions of the classical LP paradigm. However, few of these are designed as extensions of the well-established and powerful CLP scheme…

Logic in Computer Science · Computer Science 2010-09-13 Rafael Caballero , Mario Rodríguez-Artalejo , Carlos A. Romero-Díaz

Uncertainty in logic programming has been widely investigated in the last decades, leading to multiple extensions of the classical LP paradigm. However, few of these are designed as extensions of the well-established and powerful CLP scheme…

Logic in Computer Science · Computer Science 2012-01-27 R. Caballero , M. Rodriguez-Artalejo , C. A. Romero-Diaz

Similarity-based Logic Programming (briefly, SLP ) has been proposed to enhance the LP paradigm with a kind of approximate reasoning which supports flexible information retrieval applications. This approach uses a fuzzy similarity relation…

Logic in Computer Science · Computer Science 2010-08-24 Rafael Caballero , Mario Rodríguez-Artalejo , Carlos A. Romero-Díaz

Uncertainty in Logic Programming has been investigated since about 25 years, publishing papers dealing with various approaches to semantics and different applications. This report is intended as a first step towards the investigation of…

Logic in Computer Science · Computer Science 2010-08-24 Mario Rodríguez-Artalejo , Carlos A. Romero-Díaz

Constraint Logic Programming (CLP) is a logic programming formalism used to solve problems requiring the consideration of constraints, like resource allocation and automated planning and scheduling. It has previously been extended in…

Artificial Intelligence · Computer Science 2025-07-23 Jeroen Spaans , Jesse Heyninck

To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 2015 Recent advances in knowledge compilation introduced techniques to compile \emph{positive} logic programs into propositional logic, essentially exploiting…

Logic in Computer Science · Computer Science 2020-02-19 Bart Bogaerts , Guy Van den Broeck

In this paper we investigate the theoretical foundation of a new bottom-up semantics for linear logic programs, and more precisely for the fragment of LinLog that consists of the language LO enriched with the constant 1. We use constraints…

Programming Languages · Computer Science 2007-05-23 Marco Bozzano , Giorgio Delzanno , Maurizio Martelli

Higher-order constructs extend the expressiveness of first-order (Constraint) Logic Programming ((C)LP) both syntactically and semantically. At the same time assertions have been in use for some time in (C)LP systems helping programmers…

Programming Languages · Computer Science 2014-04-17 Nataliia Stulova , José F. Morales , Manuel V. Hermenegildo

Constraint logic grammars provide a powerful formalism for expressing complex logical descriptions of natural language phenomena in exact terms. Describing some of these phenomena may, however, require some form of graded distinctions which…

cmp-lg · Computer Science 2008-02-03 Stefan Riezler

Higher-order constructs extend the expressiveness of first-order (Constraint) Logic Programming ((C)LP) both syntactically and semantically. At the same time assertions have been in use for some time in (C)LP systems helping programmers…

Programming Languages · Computer Science 2014-06-03 Nataliia Stulova , José F. Morales , Manuel V. Hermenegildo

Part of the theory of logic programming and nonmonotonic reasoning concerns the study of fixed-point semantics for these paradigms. Several different semantics have been proposed during the last two decades, and some have been more…

Artificial Intelligence · Computer Science 2007-05-23 Pascal Hitzler , Matthias Wendt

We define a novel, extensional, three-valued semantics for higher-order logic programs with negation. The new semantics is based on interpreting the types of the source language as three-valued Fitting-monotonic functions at all levels of…

Programming Languages · Computer Science 2019-07-25 Angelos Charalambidis , Panos Rondogiannis , Ioanna Symeonidou

The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules…

Artificial Intelligence · Computer Science 2007-05-23 Alejandro Javier Garcia , Guillermo Ricardo Simari

Logic programming with tabling and constraints (TCLP, tabled constraint logic programming) has been shown to be more expressive and, in some cases, more efficient than LP, CLP, or LP with tabling. In this paper we provide insights regarding…

Logic in Computer Science · Computer Science 2020-10-01 Joaquín Arias , Manuel Carro

This study introduces a significance testing-enhanced conformal prediction (CP) framework to improve trustworthiness of large language models (LLMs) in multiple-choice question answering (MCQA). While LLMs have been increasingly deployed in…

Computation and Language · Computer Science 2025-08-15 Yuanchang Ye

This paper proposes the use of Constraint Logic Programming (CLP) to model SQL queries in a data-independent abstract layer by focusing on some semantic properties for signalling possible errors in such queries. First, we define a…

Databases · Computer Science 2020-02-19 Fernando Sáenz-Pérez

Constraint Logic Programming (CLP) is a language scheme for combining two declarative paradigms: constraint solving and logic programming. Concurrent Constraint Programming (CCP) is a declarative model for concurrency where agents interact…

Logic in Computer Science · Computer Science 2018-12-03 Moreno Falaschi , Carlos Olarte

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

Large Reasoning Models (LRMs) have recently demonstrated significant improvements in complex reasoning. While quantifying generation uncertainty in LRMs is crucial, traditional methods are often insufficient because they do not provide…

Artificial Intelligence · Computer Science 2026-04-16 Yangyi Li , Chenxu Zhao , Mengdi Huai
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