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Related papers: A Brief History of Updates of Answer-Set Programs

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There are some recent approaches and results about the use of answer-set programming for specifying counterfactual interventions on entities under classification, and reasoning about them. These approaches are flexible and modular in that…

Artificial Intelligence · Computer Science 2021-08-26 Leopoldo Bertossi

This paper introduces a fundamental result, which is relevant for Answer Set programming, and planning. For the first time since the definition of the stable model semantics, the class of logic programs for which a stable model exists is…

Artificial Intelligence · Computer Science 2007-05-23 Stefania Costantini

Answer Set Programming Modulo Theories (ASPMT) is a new framework of tight integration of answer set programming (ASP) and satisfiability modulo theories (SMT). Similar to the relationship between first-order logic and SMT, it is based on a…

Artificial Intelligence · Computer Science 2025-07-08 Joohyung Lee , Yunsong Meng

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

In this paper we reexamine the place and role of stable model semantics in logic programming and contrast it with a least Herbrand model approach to Horn programs. We demonstrate that inherent features of stable model semantics naturally…

Logic in Computer Science · Computer Science 2007-05-23 Victor W. Marek , Miroslaw Truszczynski

We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a ``best'' answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a…

Logic in Computer Science · Computer Science 2007-05-23 Davy Van Nieuwenborgh , Dirk Vermeir

Large Language Models~(LLMs) struggle with providing current information due to the outdated pre-training data. Existing methods for updating LLMs, such as knowledge editing and continual fine-tuning, have significant drawbacks in…

Computation and Language · Computer Science 2024-02-12 Pengfei Yu , Heng Ji

The model editing problem concerns how language models should learn new facts about the world over time. While empirical research on model editing has drawn widespread attention, the conceptual foundations of model editing remain shaky --…

Computation and Language · Computer Science 2024-06-28 Peter Hase , Thomas Hofweber , Xiang Zhou , Elias Stengel-Eskin , Mohit Bansal

Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of satisfiability modulo theories. Yet, the exact formal link…

Logic in Computer Science · Computer Science 2017-02-27 Yuliya Lierler , Benjamin Susman

We briefly describe -- mainly through very simple examples -- different kinds of answer-set programs with annotations that have been proposed for specifying: database repairs and consistent query answering; secrecy view and query evaluation…

Logic in Computer Science · Computer Science 2022-09-27 Leopoldo Bertossi

Repeated executions of reasoning tasks for varying inputs are necessary in many applicative settings, such as stream reasoning. In this context, we propose an incremental grounding approach for the answer set semantics. We focus on the…

Artificial Intelligence · Computer Science 2020-02-19 Francesco Calimeri , Giovambattista Ianni , Francesco Pacenza , Simona Perri , Jessica Zangari

Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there are definite programs and constraint logic programs that compute a solution as an answer substitution to a query…

Logic in Computer Science · Computer Science 2007-05-23 Nikolay Pelov , Emmanuel De Mot , Maurice Bruynooghe

Computational interpretations of linear logic allow static control of memory resources: the data produced by the program are endowed through its type with attributes that determine its life cycle. This has promoted numerous investigations…

Programming Languages · Computer Science 2024-08-23 Hector Gramaglia

In Knowledge Representation, it is crucial that knowledge engineers have a good understanding of the formal expressions that they write. What formal expressions state intuitively about the domain of discourse is studied in the theory of the…

Artificial Intelligence · Computer Science 2019-01-29 Marc Denecker , Yuliya Lierler , Miroslaw truszczynski , Joost Vennekens

Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabilistic argumentation frameworks provide modelling tools to…

Artificial Intelligence · Computer Science 2023-04-18 Pietro Totis , Angelika Kimmig , Luc De Raedt

Most approaches for repairing description logic (DL) ontologies aim at changing the axioms as little as possible while solving inconsistencies, incoherences and other types of undesired behaviours. As in Belief Change, these issues are…

Logic in Computer Science · Computer Science 2022-02-22 Jandson S. Ribeiro , Ricardo Guimarães , Ana Ozaki

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

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

A belief base revision is developed. The belief base is represented using Unified Answer Set Programs which is capable of representing imprecise and uncertain information and perform nonomonotonic reasoning with them. The base revision…

Artificial Intelligence · Computer Science 2020-11-24 Kumar Sankar Ray , Sandip Paul , Diganta Saha

Many machine learning algorithms rely on iterative updates of uncertainty representations, ranging from variational inference and expectation-maximization, to reinforcement learning, continual learning, and multi-agent learning. In the…

Machine Learning · Computer Science 2026-02-05 Michele Caprio , Siu Lun Chau , Krikamol Muandet