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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

Instruction-tuned large language models (LLMs) are capable of generating stories in response to open-ended user requests, but the resulting stories tend to be limited in their diversity. Older, symbolic approaches to story generation (such…

Computation and Language · Computer Science 2024-07-23 Phoebe J. Wang , Max Kreminski

Rules complement and extend ontologies on the Semantic Web. We refer to these rules as onto-relational since they combine DL-based ontology languages and Knowledge Representation formalisms supporting the relational data model within the…

Artificial Intelligence · Computer Science 2012-10-30 Francesca A. Lisi

Natural Language Processing (NLP) has become one of the leading application areas in the current Artificial Intelligence boom. Transfer learning has enabled large deep learning neural networks trained on the language modeling task to vastly…

Computation and Language · Computer Science 2022-06-16 Csaba Veres

Answer Set Programming (ASP) is an increasingly popular framework for declarative programming that admits the description of problems by means of rules and constraints that form a disjunctive logic program. In particular, many AI problems…

Computational Complexity · Computer Science 2014-03-07 Johannes Klaus Fichte , Stefan Szeider

In ontology-based data access, databases are connected to an ontology via mappings from queries over the database to queries over the ontology. In this paper, we consider mappings from relational databases to first-order ontologies, and…

Artificial Intelligence · Computer Science 2016-07-08 Daniel P. Lupp , Evgenij Thorstensen

Answer Set Programming (ASP) with stable model semantics has proven highly effective for knowledge representation and reasoning. However, the minimality requirement of stable models can be restrictive for applications requiring exploration…

Logic in Computer Science · Computer Science 2026-01-30 Fang Li , Gopal Gupta

Answer set programming (ASP) is a well-established knowledge representation formalism. Most ASP solvers are based on (extensions of) technology from Boolean satisfiability solving. While these solvers have shown to be very successful in…

Logic in Computer Science · Computer Science 2020-09-23 Wolf De Wulf , Bart Bogaerts

This paper proposes the use of Constraint Logic Programming (CLP) to model SQL queries in a data-independent abstract layer by focusing on some semantic properties for signalling possible errors in such queries. First, we define a…

Databases · Computer Science 2020-02-19 Fernando Sáenz-Pérez

On the Semantic Web, metadata and ontologies are used to enable computers to read data. The Web Ontology Language (OWL) has been proposed as a standard ontological language, and various inference systems for this language have been studied.…

Logic in Computer Science · Computer Science 2022-08-11 Daiki Takahashi , Ken Kaneiwa

Semantic embedding of knowledge graphs has been widely studied and used for prediction and statistical analysis tasks across various domains such as Natural Language Processing and the Semantic Web. However, less attention has been paid to…

Artificial Intelligence · Computer Science 2021-01-26 Jiaoyan Chen , Pan Hu , Ernesto Jimenez-Ruiz , Ole Magnus Holter , Denvar Antonyrajah , Ian Horrocks

Many applications require complexly structured data objects. Developing new or adapting existing algorithmic solutions for creating such objects can be a non-trivial and costly task if the considered objects are subject to different…

Programming Languages · Computer Science 2015-03-19 Johannes Oetsch , Jörg Pührer , Hans Tompits

This paper presents our work on development of OWL-driven systems for formal representation and reasoning about terminological knowledge and facts in petrology. The long-term aim of our project is to provide solid foundations for a…

Artificial Intelligence · Computer Science 2011-06-09 Alex Shkotin , Vladimir Ryakhovsky , Dmitry Kudryavtsev

Answer Set Programming (ASP) is a declarative logic programming formalism, which is employed nowadays in both academic and industrial real-world applications. Although some tools for supporting the development of ASP programs have been…

Programming Languages · Computer Science 2011-08-30 Onofrio Febbraro , Nicola Leone , Kristian Reale , Francesco Ricca

Answer set programming (ASP) is an efficient problem-solving approach, which has been strongly supported both scientifically and technologically by several solvers, ongoing active research, and implementations in many different fields.…

Artificial Intelligence · Computer Science 2021-09-20 Ezgi Iraz Su

Open answer set programming (OASP) is an extension of answer set programming where one may ground a program with an arbitrary superset of the program's constants. We define a fixed point logic (FPL) extension of Clark's completion such that…

Artificial Intelligence · Computer Science 2007-05-23 Stijn Heymans , Davy Van Nieuwenborgh , Dirk Vermeir

This paper explores the contributions of Answer Set Programming (ASP) to the study of an established theory from the field of Second Language Acquisition: Input Processing. The theory describes default strategies that learners of a second…

Artificial Intelligence · Computer Science 2020-02-19 Daniela Inclezan

This paper describes the analysis of a selected testbed of Semantic Web ontologies, by a SPARQL query, which determines those ontologies that can be related to the description logic DL<ForAllPiZero>, introduced in [4] and studied in [9]. We…

Artificial Intelligence · Computer Science 2012-11-26 Antonio Pisasale , Domenico Cantone

In this paper, we introduce a novel interpreting framework that learns an interpretable model based on an ontology-based sampling technique to explain agnostic prediction models. Different from existing approaches, our algorithm considers…

Machine Learning · Computer Science 2020-04-02 Phung Lai , NhatHai Phan , Han Hu , Anuja Badeti , David Newman , Dejing Dou

We introduce ontology-to-tools compilation as a proof-of-principle mechanism for coupling large language models (LLMs) with formal domain knowledge. Within The World Avatar (TWA), ontological specifications are compiled into executable tool…

Artificial Intelligence · Computer Science 2026-02-04 Xiaochi Zhou , Patrick Bulter , Changxuan Yang , Simon D. Rihm , Thitikarn Angkanaporn , Jethro Akroyd , Sebastian Mosbach , Markus Kraft
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