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Answer set programming is a leading declarative constraint programming paradigm with wide use for complex knowledge-intensive applications. Modern answer set programming languages support many equivalent ways to model constraints and…

Artificial Intelligence · Computer Science 2020-09-23 Michael Dingess , Miroslaw Truszczynski

The logical semantics of normal logic programs has traditionally been based on the notions of Clark's completion and two-valued or three-valued canonical models, including supported, stable, regular, and well-founded models. Two-valued…

Logic in Computer Science · Computer Science 2026-01-08 Van-Giang Trinh , Sylvain Soliman , François Fages , Belaid Benhamou

We introduce an implementation of an extension of Answer Set Programming (ASP) with language constructs from dynamic (and temporal) logic that provides an expressive computational framework for modeling dynamic applications. Starting from…

Artificial Intelligence · Computer Science 2020-02-20 Pedro Cabalar , Martín Diéguez , Torsten Schaub , François Laferrière

Logic programs under the stable model semantics, or answer-set programs, provide an expressive rule-based knowledge representation framework, featuring a formal, declarative and well-understood semantics. However, handling the evolution of…

Artificial Intelligence · Computer Science 2020-02-19 Martin Slota , João Leite

Timed Concurrent Constraint Programming (tcc) is a declarative model for concurrency offering a logic for specifying reactive systems, i.e. systems that continuously interact with the environment. The universal tcc formalism (utcc) is an…

Logic in Computer Science · Computer Science 2020-02-19 Moreno Falaschi , Carlos Olarte , Catuscia Palamidessi

Combining a set of existing constraint solvers into an integrated system of cooperating solvers is a useful and economic principle to solve hybrid constraint problems. In this paper we show that this approach can also be used to integrate…

Programming Languages · Computer Science 2007-05-23 Petra Hofstedt , Peter Pepper

In this thesis, we present two approaches to a rigorous mathematical and algorithmic foundation of quantitative and statistical inference in constraint-based natural language processing. The first approach, called quantitative constraint…

Computation and Language · Computer Science 2007-05-23 Stefan Riezler

Answer Set Programming (ASP) is a declarative problem solving paradigm that can be used to encode a combinatorial problem as a logic program whose stable models correspond to the solutions of the considered problem. ASP has been widely…

Logic in Computer Science · Computer Science 2024-07-15 Van-Giang Trinh , Belaid Benhamou

Many AI synthesis problems such as planning or scheduling may be modelized as constraint satisfaction problems (CSP). A CSP is typically defined as the problem of finding any consistent labeling for a fixed set of variables satisfying all…

Artificial Intelligence · Computer Science 2013-03-25 Thomas Schiex

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

Answer Set Programming (ASP) is an increasingly popular framework for declarative programming that admits the description of problems by means of rules and constraints that form a disjunctive logic program. In particular, many AI problems…

Computational Complexity · Computer Science 2014-03-07 Johannes Klaus Fichte , Stefan Szeider

ASP(Q) extends Answer Set Programming (ASP) with Quantifiers over answer sets. In this paper we focus on the class of ASP(Q) programs with two quantifiers and weak constraints, denoted as 2-ASP(Q)^w. 2-ASP(Q)^w is a practically relevant…

Artificial Intelligence · Computer Science 2026-05-27 Andrea Cuteri , Giuseppe Mazzotta , Francesco Ricca

In this paper, we propose a variant of Answer Set Programming (ASP) with evaluable functions that extends their application to sets of objects, something that allows a fully logical treatment of aggregates. Formally, we start from the…

Artificial Intelligence · Computer Science 2018-05-03 Pedro Cabalar , Jorge Fandinno , Luis Fariñas del Cerro , David Pearce

Weighted counting problems are a natural generalization of counting problems where a weight is associated with every computational path of polynomial-time non-deterministic Turing machines and the goal is to compute the sum of the weights…

Computational Complexity · Computer Science 2019-01-11 Cassio P. de Campos , Georgios Stamoulis , Dennis Weyland

Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly…

Artificial Intelligence · Computer Science 2021-08-10 Tuomo Lehtonen , Johannes P. Wallner , Matti Järvisalo

Answer Set Programming Modulo Theories (ASPMT) is an approach to combining answer set programming and satisfiability modulo theories based on the functional stable model semantics. It is shown that the tight fragment of ASPMT programs can…

Artificial Intelligence · Computer Science 2025-06-13 Michael Bartholomew , Joohyung Lee

Formal argumentation is being used increasingly in artificial intelligence as an effective and understandable way to model potentially conflicting pieces of information, called arguments, and identify so-called acceptable arguments…

Artificial Intelligence · Computer Science 2026-03-09 Yann Munro , Isabelle Bloch , Marie-Jeanne Lesot

We present a scheme for translating logic programs, which may use aggregation and arithmetic, into algebraic expressions that denote bag relations over ground terms of the Herbrand universe. To evaluate queries against these relations, we…

Programming Languages · Computer Science 2020-10-21 Matthew Francis-Landau , Tim Vieira , Jason Eisner

It is widely acknowledged that function symbols are an important feature in answer set programming, as they make modeling easier, increase the expressive power, and allow us to deal with infinite domains. The main issue with their…

Artificial Intelligence · Computer Science 2020-02-19 Marco Calautti , Sergio Greco , Cristian Molinaro , Irina Trubitsyna

We study the complexity of constraint satisfaction problems involving global constraints, i.e., special-purpose constraints provided by a solver and represented implicitly by a parametrised algorithm. Such constraints are widely used;…

Artificial Intelligence · Computer Science 2013-07-11 David A. Cohen , Peter G. Jeavons , Evgenij Thorstensen , Stanislav Živný
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