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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

Weighted monadic second-order logic is a weighted extension of monadic second-order logic that captures exactly the behaviour of weighted automata. Its semantics is parameterized with respect to a semiring on which the values that weighted…

Logic in Computer Science · Computer Science 2021-04-30 Antonis Achilleos , Mathias Ruggaard Pedersen

Answer Set Programming (ASP) is a widely used declarative programming paradigm that has shown great potential in solving complex computational problems. However, the inability to natively support non-integer arithmetic has been highlighted…

Artificial Intelligence · Computer Science 2023-12-08 Francesco Pacenza , Jessica Zangari

In answer set programming (ASP), a problem at hand is solved by (i) writing a logic program whose answer sets correspond to the solutions of the problem, and by (ii) computing the answer sets of the program using an answer set solver as a…

Artificial Intelligence · Computer Science 2007-05-23 Tomi Janhunen , Emilia Oikarinen

We characterize the inclusions of weighted classes of entire functions in terms of the defining weights resp. weight systems. First we treat weights defined in terms of a so-called associated weight function where the weight(system) is…

Complex Variables · Mathematics 2024-01-24 Gerhard Schindl

We propose abstract compilation for precise static type analysis of object-oriented languages based on coinductive logic programming. Source code is translated to a logic program, then type-checking and inference problems amount to queries…

Programming Languages · Computer Science 2017-09-15 Luca Franceschini , Davide Ancona , Ekaterina Komendantskaya

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

In this work we propose a multi-valued extension of logic programs under the stable models semantics where each true atom in a model is associated with a set of justifications, in a similar spirit than a set of proof trees. The main…

Artificial Intelligence · Computer Science 2013-12-24 Pedro Cabalar , Jorge Fandinno

Recursive definitions of predicates are usually interpreted either inductively or coinductively. Recently, a more powerful approach has been proposed, called flexible coinduction, to express a variety of intermediate interpretations,…

Programming Languages · Computer Science 2020-09-23 Francesco Dagnino , Davide Ancona , Elena Zucca

Reasoning about dynamic systems with a fine-grained temporal and numeric resolution presents significant challenges for logic-based approaches like Answer Set Programming (ASP). To address this, we introduce and elaborate upon a novel…

Artificial Intelligence · Computer Science 2026-01-14 Pedro Cabalar , Martín Diéguez , François Olivier , Torsten Schaub , Igor Stéphan

Many real life optimization problems contain both hard and soft constraints, as well as qualitative conditional preferences. However, there is no single formalism to specify all three kinds of information. We therefore propose a framework,…

Artificial Intelligence · Computer Science 2009-05-26 Carmel Domshlak , Francesca Rossi , Kristen Brent Venable , Toby Walsh

Formal deductive systems are very common in computer science. They are used to represent logics, programming languages, and security systems. Moreover, writing programs that manipulate them and that reason about them is important and…

Programming Languages · Computer Science 2018-05-21 Francisco Ferreira Ruiz

Answer Set Programming (ASP), a well-known declarative logic programming paradigm, has recently found practical application in Process Mining. In particular, ASP has been used to model tasks involving declarative specifications of business…

Logic in Computer Science · Computer Science 2025-02-19 Francesco Chiariello , Valeria Fionda , Antonio Ielo , Francesco Ricca

A core challenge in program synthesis is taming the large space of possible programs. Since program synthesis is essentially a combinatorial search, the community has sought to leverage powerful combinatorial constraint solvers. Here,…

Answer Set Programming (ASP) is a declarative programming language used for modeling and solving complex combinatorial problems. It has been successfully applied to a number of different realworld problems. However, learning its usage can…

Software Engineering · Computer Science 2026-03-31 Rafael Martins , Matthias Knorr , Ricardo Gonçalves

This technical note describes a monotone and continuous fixpoint operator to compute the answer sets of programs with aggregates. The fixpoint operator relies on the notion of aggregate solution. Under certain conditions, this operator…

Artificial Intelligence · Computer Science 2007-05-23 Tran Cao Son , Enrico Pontelli

A relational database is inconsistent if it does not satisfy a given set of integrity constraints. Nevertheless, it is likely that most of the data in it is consistent with the constraints. In this paper we apply logic programming based on…

Databases · Computer Science 2007-05-23 Marcelo Arenas , Leopoldo Bertossi , Jan Chomicki

Constraint programming is a family of techniques for solving combinatorial problems, where the problem is modelled as a set of decision variables (typically with finite domains) and a set of constraints that express relations among the…

Artificial Intelligence · Computer Science 2016-05-31 James Caldwell , Ian P. Gent , Peter Nightingale

We examine the practicality for a user of using Answer Set Programming (ASP) for representing logical formalisms. We choose as an example a formalism aiming at capturing causal explanations from causal information. We provide an…

Artificial Intelligence · Computer Science 2010-12-06 Yves Moinard

Qualitative reasoning involves expressing and deriving knowledge based on qualitative terms such as natural language expressions, rather than strict mathematical quantities. Well over 40 qualitative calculi have been proposed so far, mostly…

Artificial Intelligence · Computer Science 2025-12-17 George Baryannis , Ilias Tachmazidis , Sotiris Batsakis , Grigoris Antoniou , Mario Alviano , Emmanuel Papadakis