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While large language models (LLMs), such as GPT-3, appear to be robust and general, their reasoning ability is not at a level to compete with the best models trained for specific natural language reasoning problems. In this study, we…

Computation and Language · Computer Science 2023-07-18 Zhun Yang , Adam Ishay , Joohyung Lee

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

We introduce a new flexible paradigm of grounding and solving in Answer Set Programming (ASP), which we refer to as multi-shot ASP solving, and present its implementation in the ASP system clingo. Multi-shot ASP solving features grounding…

Artificial Intelligence · Computer Science 2018-03-21 Martin Gebser , Roland Kaminski , Benjamin Kaufmann , Torsten Schaub

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

Artificial Intelligence (AI) approaches to problem-solving and decision-making are becoming more and more complex, leading to a decrease in the understandability of solutions. The European Union's new General Data Protection Regulation…

Artificial Intelligence · Computer Science 2018-09-24 Jorge Fandinno , Claudia Schulz

This paper describes a system, called PLP, for compiling ordered logic programs into standard logic programs under the answer set semantics. In an ordered logic program, rules are named by unique terms, and preferences among rules are given…

Artificial Intelligence · Computer Science 2007-05-23 James P. Delgrande , Torsten Schaub , Hans Tompits

We propose relational linear programming, a simple framework for combing linear programs (LPs) and logic programs. A relational linear program (RLP) is a declarative LP template defining the objective and the constraints through the logical…

Artificial Intelligence · Computer Science 2014-10-14 Kristian Kersting , Martin Mladenov , Pavel Tokmakov

Weighted Logic is a powerful tool for the specification of calculations over semirings that depend on qualitative information. Using a novel combination of Weighted Logic and Here-and-There (HT) Logic, in which this dependence is based on…

Artificial Intelligence · Computer Science 2022-11-14 Thomas Eiter , Rafael Kiesel

Knowledge Representation and Reasoning and Machine Learning are two important fields in AI. Nonmonotonic logic programming (NMLP) and Answer Set Programming (ASP) provide formal languages for representing and reasoning with commonsense…

Artificial Intelligence · Computer Science 2013-11-20 Katsumi Inoue , Chiaki Sakama

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

DLV2 is an AI tool for Knowledge Representation and Reasoning which supports Answer Set Programming (ASP) - a logic-based declarative formalism, successfully used in both academic and industrial applications. Given a logic program modelling…

Artificial Intelligence · Computer Science 2025-05-28 Francesco Calimeri , Giovambattista Ianni , Francesco Pacenza , Simona Perri , Jessica Zangari

Answer-Set Programming (ASP) is an established declarative programming paradigm. However, classical ASP lacks subprogram calls as in procedural programming, and access to external computations (like remote procedure calls) in general. The…

Artificial Intelligence · Computer Science 2011-09-01 Thomas Eiter , Thomas Krennwallner , Christoph Redl

Answer-Set Programming (ASP) is a powerful and expressive knowledge representation paradigm with a significant number of applications in logic-based AI. The traditional ground-and-solve approach, however, requires ASP programs to be…

Artificial Intelligence · Computer Science 2020-08-11 Antonius Weinzierl , Richard Taupe , Gerhard Friedrich

In this paper we introduce a Conditional Answer Set Programming framework (Conditional ASP) for the definition of conditional extensions of Answer Set Programming (ASP). The approach builds on a conditional logic with typicality, and on the…

Artificial Intelligence · Computer Science 2026-01-08 Mario Alviano , Laura Giordano , Daniele Theseider Dupré

Standard answer set programming (ASP) targets at solving search problems from the first level of the polynomial time hierarchy (PH). Tackling search problems beyond NP using ASP is less straightforward. The class of disjunctive logic…

Artificial Intelligence · Computer Science 2016-08-16 Bart Bogaerts , Tomi Janhunen , Shahab Tasharrofi

Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is not possible to draw any conclusion, even if this is not…

Logic in Computer Science · Computer Science 2017-07-24 Giovanni Amendola , Carmine Dodaro , Wolfgang Faber , Nicola Leone , Francesco Ricca

Our broader goal is to automatically translate English sentences into formulas in appropriate knowledge representation languages as a step towards understanding and thus answering questions with respect to English text. Our focus in this…

Artificial Intelligence · Computer Science 2012-10-23 Chitta Baral , Juraj Dzifcak , Marcos A. Gonzalez , Aaron Gottesman

In this paper, we study the problem of formal verification for Answer Set Programming (ASP), namely, obtaining a formal proof showing that the answer sets of a given (non-ground) logic program P correctly correspond to the solutions to the…

Logic in Computer Science · Computer Science 2020-09-23 Pedro Cabalar , Jorge Fandinno , Yuliya Lierler

The language of epistemic specifications and epistemic logic programs extends disjunctive logic programs under the stable model semantics with modal constructs called subjective literals. Using subjective literals, it is possible to check…

Artificial Intelligence · Computer Science 2021-10-06 Jorge Fandinno , Wolfgang Faber , Michael Gelfond

Dung's famous abstract argumentation frameworks represent the core formalism for many problems and applications in the field of argumentation which significantly evolved within the last decade. Recent work in the field has thus focused on…

Artificial Intelligence · Computer Science 2016-04-20 Wolfgang Dvořák , Sarah Alice Gaggl , Johannes Wallner , Stefan Woltran
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