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Part of the theory of logic programming and nonmonotonic reasoning concerns the study of fixed-point semantics for these paradigms. Several different semantics have been proposed during the last two decades, and some have been more…

Artificial Intelligence · Computer Science 2007-05-23 Pascal Hitzler , Matthias Wendt

This paper studies the stable model semantics of logic programs with (abstract) constraint atoms and their properties. We introduce a succinct abstract representation of these constraint atoms in which a constraint atom is represented…

Artificial Intelligence · Computer Science 2009-05-01 Yi-Dong Shen , Jia-Huai You , Li-Yan Yuan

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

This paper continues an established line of research about the relations between argumentation theory, particularly assumption-based argumentation, and different kinds of logic programs. In particular, we extend known result of Caminada,…

Artificial Intelligence · Computer Science 2025-07-09 Jesse Heyninck , Ofer Arieli

Answer Set Programming (ASP) is a declarative programming paradigm based on logic programming and non-monotonic reasoning. It is a tremendously powerful tool for describing and solving combinatorial problems. Like any other language, ASP…

Artificial Intelligence · Computer Science 2025-11-13 Connar Hite , Sean Saud , Raef Taha , Nayim Rahman , Tanvir Atahary , Scott Douglass , Tarek Taha

By incorporating the methods of Answer Set Programming (ASP) and Markov Logic Networks (MLN), LPMLN becomes a powerful tool for non-monotonic, inconsistent and uncertain knowledge representation and reasoning. To facilitate the applications…

Logic in Computer Science · Computer Science 2019-09-19 Bin Wang , Jun Shen , Shutao Zhang , Zhizheng Zhang

Answer Set Programming (ASP) is a well-known declarative formalism in logic programming. Efficient implementations made it possible to apply ASP in many scenarios, ranging from deductive databases applications to the solution of hard…

Logic in Computer Science · Computer Science 2020-02-19 Bernardo Cuteri , Carmine Dodaro , Francesco Ricca , Peter Schüller

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

In recent years, large language models (LLMs) have made significant advancements in developing human-like and engaging dialogue systems. However, in tasks such as consensus-building and persuasion, LLMs often struggle to resolve conflicts…

Artificial Intelligence · Computer Science 2025-11-14 Zhaoqun Li , Xiaotong Fang , Chen Chen , Mengze Li , Beishui Liao

Approximation fixpoint theory (AFT) is an abstract and general algebraic framework for studying the semantics of nonmonotonic logics. It provides a unifying study of the semantics of different formalisms for nonmonotonic reasoning, such as…

Artificial Intelligence · Computer Science 2022-12-02 Jesse Heyninck , Ofer Arieli , Bart Bogaerts

Logical frameworks and meta-languages form a common substrate for representing, implementing and reasoning about a wide variety of deductive systems of interest in logic and computer science. Their design, implementation and their use in…

Logic in Computer Science · Computer Science 2021-07-16 Elaine Pimentel , Enrico Tassi

Large language models (LLMs) are capable of solving a wide range of tasks, yet they have struggled with reasoning. To address this, we propose $\textbf{Additional Logic Training (ALT)}$, which aims to enhance LLMs' reasoning capabilities by…

Machine Learning · Computer Science 2024-12-24 Terufumi Morishita , Gaku Morio , Atsuki Yamaguchi , Yasuhiro Sogawa

We show that an interesting class of feed-forward neural networks can be understood as quantitative argumentation frameworks. This connection creates a bridge between research in Formal Argumentation and Machine Learning. We generalize the…

Neural and Evolutionary Computing · Computer Science 2020-12-11 Nico Potyka

Uncertain information is being taken into account in an increasing number of application fields. In the meantime, abduction has been proved a powerful tool for handling hypothetical reasoning and incomplete knowledge. Probabilistic logical…

Artificial Intelligence · Computer Science 2022-02-04 Elena Bellodi , Marco Gavanelli , Riccardo Zese , Evelina Lamma , Fabrizio Riguzzi

LPMLN is a powerful knowledge representation and reasoning tool that combines the non-monotonic reasoning ability of Answer Set Programming (ASP) and the probabilistic reasoning ability of Markov Logic Networks (MLN). In this paper, we…

Logic in Computer Science · Computer Science 2023-06-22 Bin Wang , Jun Shen , Shutao Zhang , Zhizheng Zhang

Epistemic logic programs constitute an extension of the stable models semantics to deal with new constructs called subjective literals. Informally speaking, a subjective literal allows checking whether some regular literal is true in all…

Artificial Intelligence · Computer Science 2021-07-01 Pedro Cabalar , Jorge Fandinno , Luis Fariñas del Cerro

Dung's abstract framework for argumentation enables a study of the interactions between arguments based solely on an ``attack'' binary relation on the set of arguments. Various ways to solve conflicts between contradictory pieces of…

Artificial Intelligence · Computer Science 2007-05-23 C. Cayrol , S. Doutre , M. -C. Lagasquie-Schiex , J. Mengin

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

We contemplate a higher-level bipolar abstract argumentation for non-elementary arguments such as: X argues against Ys sincerity with the fact that Y has presented his argument to draw a conclusion C, by omitting other facts which would not…

Artificial Intelligence · Computer Science 2019-01-21 Ryuta Arisaka , Stefano Bistarelli , Francesco Santini

Answer Set Programming (ASP) is a popular framework for modeling combinatorial problems. However, ASP cannot easily be used for reasoning about uncertain information. Possibilistic ASP (PASP) is an extension of ASP that combines…

Artificial Intelligence · Computer Science 2020-02-19 Kim Bauters , Steven Schockaert , Martine De Cock , Dirk Vermeir