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Abstract argumentation is a popular toolkit for modeling, evaluating, and comparing arguments. Relationships between arguments are specified in argumentation frameworks (AFs), and conditions are placed on sets (extensions) of arguments that…

Artificial Intelligence · Computer Science 2024-08-21 Johannes K. Fichte , Markus Hecher , Yasir Mahmood , Arne Meier

The paper presents an enhancement of xASP, a system that generates explanation graphs for Answer Set Programming (ASP). Different from xASP, the new system, xASP2, supports different clingo constructs like the choice rules, the constraints,…

Artificial Intelligence · Computer Science 2023-08-31 Mario Alviano , Ly Ly Trieu , Tran Cao Son , Marcello Balduccini

In recent years, Answer Set Programming (ASP), logic programming under the stable model or answer set semantics, has seen several extensions by generalizing the notion of an atom in these programs: be it aggregate atoms, HEX atoms,…

Artificial Intelligence · Computer Science 2013-12-23 Mario Alviano , Wolfgang Faber

Abstract solvers are a method to formally analyze algorithms that have been profitably used for describing, comparing and composing solving techniques in various fields such as Propositional Satisfiability (SAT), Quantified SAT,…

Logic in Computer Science · Computer Science 2020-02-19 Giovanni Amendola , Carmine Dodaro , Marco Maratea

Weighted knowledge bases for description logics with typicality have been recently considered under a "concept-wise" multipreference semantics (in both the two-valued and fuzzy case), as the basis of a logical semantics of MultiLayer…

Artificial Intelligence · Computer Science 2022-05-18 Laura Giordano , Daniele Theseider Dupré

Decision tree models, including random forests and gradient-boosted decision trees, are widely used in machine learning due to their high predictive performance. However, their complex structures often make them difficult to interpret,…

Artificial Intelligence · Computer Science 2026-01-08 Akihiro Takemura , Masayuki Otani , Katsumi Inoue

Dealing with context dependent knowledge has led to different formalizations of the notion of context. Among them is the Contextualized Knowledge Repository (CKR) framework, which is rooted in description logics but links on the reasoning…

Artificial Intelligence · Computer Science 2021-12-23 Loris Bozzato , Thomas Eiter , Rafael Kiesel

We present a system capable of automatically solving combinatorial logic puzzles given in (simplified) English. It involves translating the English descriptions of the puzzles into answer set programming(ASP) and using ASP solvers to…

Computation and Language · Computer Science 2011-08-22 Chitta Baral , Juraj Dzifcak

Answer-set programming (ASP) has emerged recently as a viable programming paradigm well attuned to search problems in AI, constraint satisfaction and combinatorics. Propositional logic is, arguably, the simplest ASP system with an intuitive…

Artificial Intelligence · Computer Science 2007-05-23 Deborah East , Miroslaw Truszczynski

Cooperation among constraint solvers is difficult because different solving paradigms have different theoretical foundations. Recent works have shown that abstract interpretation can provide a unifying theory for various constraint solvers.…

Artificial Intelligence · Computer Science 2020-09-23 Pierre Talbot , Éric Monfroy , Charlotte Truchet

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

Answer Set Programming (ASP) is a well-established declarative problem solving paradigm which became widely used in AI and recognized as a powerful tool for knowledge representation and reasoning (KRR), especially for its high…

Artificial Intelligence · Computer Science 2017-07-24 Francesco Calimeri , Davide Fuscà , Stefano Germano , Simona Perri , Jessica Zangari

Answer Set Programming (ASP) is a generic problem modeling and solving framework with a strong focus on knowledge representation and a rapid growth of industrial applications. So far, the study of complexity resulted in characterizing…

Artificial Intelligence · Computer Science 2024-02-07 Markus Hecher , Rafael Kiesel

Modern scientific software stacks have become extremely complex, using many programming models and libraries to exploit a growing variety of GPUs and accelerators. Package managers can mitigate this complexity using dependency solvers, but…

Software Engineering · Computer Science 2022-10-18 Todd Gamblin , Massimiliano Culpo , Gregory Becker , Sergei Shudler

ASP programs are a convenient tool for problem solving, whereas with large problem instances the size of the state space can be prohibitive. We consider abstraction as a means of over-approximation and introduce a method to automatically…

Logic in Computer Science · Computer Science 2018-09-19 Zeynep G. Saribatur , Thomas Eiter

Answer Set Programming (ASP) is a well-known problem solving approach based on nonmonotonic logic programs. HEX-programs extend ASP with external atoms for accessing arbitrary external information, which can introduce values that do not…

Artificial Intelligence · Computer Science 2018-06-04 Christoph Redl

Abstract argumentation frameworks (AFs) are one of the most studied formalisms in AI. In this work, we introduce a certain subclass of AFs which we call compact. Given an extension-based semantics, the corresponding compact AFs are…

Artificial Intelligence · Computer Science 2014-05-01 Ringo Baumann , Wolfgang Dvorák , Thomas Linsbichler , Hannes Strass , Stefan Woltran

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

Encoding finite linear CSPs as Boolean formulas and solving them by using modern SAT solvers has proven to be highly effective, as exemplified by the award-winning sugar system. We here develop an alternative approach based on ASP. This…

Artificial Intelligence · Computer Science 2013-12-23 Mutsunori Banbara , Martin Gebser , Katsumi Inoue , Torsten Schaub , Takehide Soh , Naoyuki Tamura , Matthias Weise

We develop a computational approach to Metric Answer Set Programming (ASP) to allow for expressing quantitative temporal constrains, like durations and deadlines. A central challenge is to maintain scalability when dealing with fine-grained…

Artificial Intelligence · Computer Science 2025-06-11 Arvid Becker , Pedro Cabalar , Martin Diéguez , Javier Romero , Susana Hahn , Torsten Schaub
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