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This paper shows that the semantics of programs with aggregates implemented by the solvers clingo and dlv can be characterized as extended First-Order formulas with intensional functions in the logic of Here-and-There. Furthermore, this…

Artificial Intelligence · Computer Science 2024-12-17 Jorge Fandinno , Zachary Hansen

Answer Set Programming (ASP) emerged in the late 1990ies as a paradigm for Knowledge Representation and Reasoning. The attractiveness of ASP builds on an expressive high-level modeling language along with the availability of powerful…

Artificial Intelligence · Computer Science 2021-09-20 Mario Alviano , Wolfgang Faber , Martin Gebser

Answer set programming (ASP) is a logic programming paradigm that can be used to solve complex combinatorial search problems. Aggregates are an ASP construct that plays an important role in many applications. Defining a satisfactory…

Artificial Intelligence · Computer Science 2008-12-09 Paolo Ferraris

The paper presents two equivalent definitions of answer sets for logic programs with aggregates. These definitions build on the notion of unfolding of aggregates, and they are aimed at creating methodologies to translate logic programs with…

Software Engineering · Computer Science 2007-05-23 Tran Cao Son , Enrico Pontelli , Islam Elkabani

Aggregates provide a concise way to express complex knowledge. The problem of selecting an appropriate formalisation of aggregates for answer set programming (ASP) remains unsettled. This paper revisits it from the viewpoint of…

Artificial Intelligence · Computer Science 2022-05-18 Linde Vanbesien , Maurice Bruynooghe , Marc Denecker

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

In classical logic, nonBoolean fluents, such as the location of an object, can be naturally described by functions. However, this is not the case in answer set programs, where the values of functions are pre-defined, and nonmonotonicity of…

Artificial Intelligence · Computer Science 2023-07-21 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

In this paper we propose an extension of Answer Set Programming (ASP), and in particular, of its most general logical counterpart, Quantified Equilibrium Logic (QEL), to deal with partial functions. Although the treatment of equality in QEL…

Logic in Computer Science · Computer Science 2010-06-21 Pedro Cabalar

We elaborate upon the formal foundations of hybrid Answer Set Programming (ASP) and extend its underlying logical framework with aggregate functions over constraint values and variables. This is achieved by introducing the construct of…

Artificial Intelligence · Computer Science 2020-02-25 Pedro Cabalar , Jorge Fandinno , Torsten Schaub , Philipp Wanko

We argue that in some KR applications, we want to quantify over sets of concepts formally represented by symbols in the vocabulary. We show that this quantification should be distinguished from second-order quantification and…

Logic in Computer Science · Computer Science 2023-08-31 Pierre Carbonnelle , Matthias Van der Hallen , Marc Denecker

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

Gelfond and Zhang recently proposed a new stable model semantics based on Vicious Circle Principle in order to improve the interpretation of logic programs with aggregates. The paper focuses on this proposal, and analyzes the complexity of…

Artificial Intelligence · Computer Science 2020-02-19 Mario Alviano , Nicola Leone

Answer Set Programming (ASP) is a truly-declarative programming paradigm proposed in the area of non-monotonic reasoning and logic programming, that has been recently employed in many applications. The development of efficient ASP systems…

Artificial Intelligence · Computer Science 2020-02-19 Marco Maratea , Luca Pulina , Francesco Ricca

Significant research has been conducted in recent years to extend Inductive Logic Programming (ILP) methods to induce Answer Set Programs (ASP). These methods perform an exhaustive search for the correct hypothesis by encoding an ILP…

Logic in Computer Science · Computer Science 2018-02-20 Farhad Shakerin , Gopal Gupta

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 logic programming under the stable model or answer set semantics. During the last decade, this paradigm has seen several extensions by generalizing the notion of atom used in these programs. Among these,…

Artificial Intelligence · Computer Science 2014-05-07 Mario Alviano , Wolfgang Faber

Answer Set Programming (ASP) is a logic programming paradigm featuring a purely declarative language with comparatively high modeling capabilities. Indeed, ASP can model problems in NP in a compact and elegant way. However, modeling…

Artificial Intelligence · Computer Science 2020-02-19 Giovanni Amendola , Francesco Ricca , Mirek Truszczynski

We propose a new formal language for the expressive representation of probabilistic knowledge based on Answer Set Programming (ASP). It allows for the annotation of first-order formulas as well as ASP rules and facts with probabilities and…

Artificial Intelligence · Computer Science 2014-05-06 Matthias Nickles , Alessandra Mileo

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
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