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An important issue towards a broader acceptance of answer-set programming (ASP) is the deployment of tools which support the programmer during the coding phase. In particular, methods for debugging an answer-set program are recognised as a…

Programming Languages · Computer Science 2010-07-29 Johannes Oetsch , Jörg Pührer , Hans Tompits

Possibilistic answer set programming (PASP) extends answer set programming (ASP) by attaching to each rule a degree of certainty. While such an extension is important from an application point of view, existing semantics are not…

Artificial Intelligence · Computer Science 2012-03-19 Kim Bauters , Steven Schockaert , Martine De Cock , Dirk Vermeir

Answer Set Programming (ASP) is a powerful logic-based programming language, which is enjoying increasing interest within the scientific community and (very recently) in industry. The evaluation of ASP programs is traditionally carried out…

Programming Languages · Computer Science 2011-10-14 Simona Perri , Francesco Ricca , Marco Sirianni

Answer set programming (ASP) is a popular declarative programming paradigm with various applications. Programs can easily have many answer sets that cannot be enumerated in practice, but counting still allows quantifying solution spaces. If…

Artificial Intelligence · Computer Science 2023-11-14 Johannes K. Fichte , Sarah Alice Gaggl , Markus Hecher , Dominik Rusovac

This article presents the use of Answer Set Programming (ASP) to mine sequential patterns. ASP is a high-level declarative logic programming paradigm for high level encoding combinatorial and optimization problem solving as well as…

Artificial Intelligence · Computer Science 2017-11-15 Thomas Guyet , Yves Moinard , René Quiniou , Torsten Schaub

A fundamental question in systems biology is the construction and training to data of mathematical models. Logic formalisms have become very popular to model signaling networks because their simplicity allows us to model large systems…

Quantitative Methods · Quantitative Biology 2012-12-27 Santiago Videla , Carito Guziolowski , Federica Eduati , Sven Thiele , Niels Grabe , Julio Saez-Rodriguez , Anne Siegel

Large Language Models (LLMs) excel at understanding natural language but struggle with explicit commonsense reasoning. A recent trend of research suggests that the combination of LLM with robust symbolic reasoning systems can overcome this…

Artificial Intelligence · Computer Science 2025-09-23 Manuel Borroto , Katie Gallagher , Antonio Ielo , Irfan Kareem , Francesco Ricca , Alessandra Russo

As a programming paradigm, answer set programming (ASP) brings about the usual issue of the human error. Hence, it is desirable to provide automated techniques that could help the programmer to find the error. This paper addresses the…

Logic in Computer Science · Computer Science 2014-07-01 Mikoláš Janota , Joao Marques-Silva

Dung's famous abstract argumentation frameworks represent the core formalism for many problems and applications in the field of argumentation which significantly evolved within the last decade. Recent work in the field has thus focused on…

Artificial Intelligence · Computer Science 2016-04-20 Wolfgang Dvořák , Sarah Alice Gaggl , Johannes Wallner , Stefan Woltran

Recently, Large Language Models (LLMs) have showcased their potential in various natural language processing tasks, including code generation. However, while significant progress has been made in adapting LLMs to generate code for several…

Machine Learning · Computer Science 2024-07-29 Erica Coppolillo , Francesco Calimeri , Giuseppe Manco , Simona Perri , Francesco Ricca

Answer Set Programming (ASP) is a powerful tool for solving real-world problems. However, many problems involve numeric values and complex constraints beyond the capabilities of standard ASP solvers. Hybrid solvers like CLINGCON and…

Artificial Intelligence · Computer Science 2025-02-14 Nicolas Rühling

ACLP is a system which combines abductive reasoning and constraint solving by integrating the frameworks of Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP). It forms a general high-level knowledge representation…

Artificial Intelligence · Computer Science 2007-05-23 Antonis Kakas

Knowledge Representation and Reasoning and Machine Learning are two important fields in AI. Nonmonotonic logic programming (NMLP) and Answer Set Programming (ASP) provide formal languages for representing and reasoning with commonsense…

Artificial Intelligence · Computer Science 2013-11-20 Katsumi Inoue , Chiaki Sakama

Disjunctive Logic Programming (DLP) is a very expressive formalism: it allows for expressing every property of finite structures that is decidable in the complexity class SigmaP2 (= NP^NP). Despite this high expressiveness, there are some…

Artificial Intelligence · Computer Science 2008-02-22 Wolfgang Faber , Gerald Pfeifer , Nicola Leone , Tina Dell'Armi , Giuseppe Ielpa

The explication and the generation of explanations are prominent topics in artificial intelligence and data science, in order to make methods and systems more transparent and understandable for humans. This paper investigates the problem of…

Artificial Intelligence · Computer Science 2019-09-10 Martin Atzmueller , Cicek Güven , Dietmar Seipel

In this paper we present a dependency graph-based method for computing the various semantics of normal logic programs. Our method employs \textit{conjunction nodes} to unambiguously represent the dependency graph of normal logic programs.…

Logic in Computer Science · Computer Science 2021-11-29 Fang Li , Elmer Salazar , Gopal Gupta

Researchers in answer set programming and constraint programming have spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts…

Artificial Intelligence · Computer Science 2017-12-04 Marcello Balduccini , Yuliya Lierler

Answer Set Programming (ASP) is a well-established paradigm of declarative programming that has been developed in the field of logic programming and nonmonotonic reasoning. Advances in ASP solving technology are customarily assessed in…

Artificial Intelligence · Computer Science 2014-06-04 Francesco Calimeri , Martin Gebser , Marco Maratea , Francesco Ricca

Goal-directed evaluation of Answer Set Programs is gaining traction thanks to its amenability to create AI systems that can, due to the evaluation mechanism used, generate explanations and justifications. s(CASP) is one of these systems and…

Artificial Intelligence · Computer Science 2021-10-26 Joaquín Arias , Manuel Carro , Gopal Gupta

In this paper, we present two alternative approaches to defining answer sets for logic programs with arbitrary types of abstract constraint atoms (c-atoms). These approaches generalize the fixpoint-based and the level mapping based answer…

Artificial Intelligence · Computer Science 2011-10-12 E. Pontelli , T. C. Son , P. H. Tu
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