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As ontologies and description logics (DLs) reach out to a broader audience, several reasoning services are developed in this context. Belief revision is one of them, of prime importance when knowledge is prone to change and inconsistency.…

Artificial Intelligence · Computer Science 2015-02-27 Marc Aiguier , Jamal Atif , Isabelle Bloch , Céline Hudelot

Magic sets are a Datalog to Datalog rewriting technique to optimize query answering. The rewritten program focuses on a portion of the stable model(s) of the input program which is sufficient to answer the given query. However, the…

Artificial Intelligence · Computer Science 2020-02-19 Mario Alviano , Nicola Leone , Pierfrancesco Veltri , Jessica Zangari

The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. In this paper, we argue that to apply rationality result of belief dynamics theory to…

Logic in Computer Science · Computer Science 2014-07-22 Radhakrishnan Delhibabu , Gerhard Lakemeyer

A common assumption in belief revision is that the reliability of the information sources is either given, derived from temporal information, or the same for all. This article does not describe a new semantics for integration but the…

Artificial Intelligence · Computer Science 2021-04-09 Paolo Liberatore

Large language models (LLMs), such as GPT-3 and GPT-4, have demonstrated exceptional performance in various natural language processing tasks and have shown the ability to solve certain reasoning problems. However, their reasoning…

Artificial Intelligence · Computer Science 2023-07-18 Adam Ishay , Zhun Yang , Joohyung Lee

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

Abductive logic programming offers a formalism to declaratively express and solve problems in areas such as diagnosis, planning, belief revision and hypothetical reasoning. Tabled logic programming offers a computational mechanism that…

Logic in Computer Science · Computer Science 2016-08-15 José Júlio Alferes , Luís Moniz Pereira , Terrance Swift

It is well known that, under certain conditions, it is possible to split logic programs under stable model semantics, i.e. to divide such a program into a number of different "levels", such that the models of the entire program can be…

Artificial Intelligence · Computer Science 2007-05-23 Joost Vennekens , David Gilis , Marc Denecker

The field of probabilistic logic programming (PLP) focuses on integrating probabilistic models into programming languages based on logic. Over the past 30 years, numerous languages and frameworks have been developed for modeling, inference…

Artificial Intelligence · Computer Science 2024-02-22 Vincent Derkinderen , Robin Manhaeve , Pedro Zuidberg Dos Martires , Luc De Raedt

Rules in logic programming encode information about mutual interdependencies between literals that is not captured by any of the commonly used semantics. This information becomes essential as soon as a program needs to be modified or…

Artificial Intelligence · Computer Science 2011-03-02 Martin Slota , João Leite

This paper deals with belief base revision that is a form of belief change consisting of the incorporation of new facts into an agent's beliefs represented by a finite set of propositional formulas. In the aim to guarantee more reliability…

Artificial Intelligence · Computer Science 2020-09-25 Raïda Ktari , Mohamed Ayman Boujelben

We investigate mca-programs, that is, logic programs with clauses built of monotone cardinality atoms of the form kX, where k is a non-negative integer and X is a finite set of propositional atoms. We develop a theory of mca-programs. We…

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

The study of belief change has been an active area in philosophy and AI. In recent years two special cases of belief change, belief revision and belief update, have been studied in detail. In a companion paper (Friedman & Halpern, 1997), we…

Artificial Intelligence · Computer Science 2007-05-23 N Friedman , J. Y. Halpern

Although pretrained language models (PTLMs) contain significant amounts of world knowledge, they can still produce inconsistent answers to questions when probed, even after specialized training. As a result, it can be hard to identify what…

Computation and Language · Computer Science 2021-10-01 Nora Kassner , Oyvind Tafjord , Hinrich Schütze , Peter Clark

This paper presents a method of computing a revision of a function-free normal logic program. If an added rule is inconsistent with a program, that is, if it leads to a situation such that no stable model exists for a new program, then…

Artificial Intelligence · Computer Science 2007-05-23 Ken Satoh

This note points out a lemma on closures of monotonic increasing functions and shows how it is applicable to decomposition and modularity for semantics defined as the least fixedpoint of some monotonic function. In particular it applies to…

Logic in Computer Science · Computer Science 2020-08-04 Michael J. Maher

Answer Set Programming (ASP) is a prominent problem-modeling and solving framework, whose solutions are called answer sets. Epistemic logic programs (ELP) extend ASP to reason about all or some answer sets. Solutions to an ELP can be seen…

Logic in Computer Science · Computer Science 2025-03-10 Thomas Eiter , Johannes K. Fichte , Markus Hecher , Stefan Woltran

Answer set programming (ASP) is a well-established logic programming language that offers an intuitive, declarative syntax for problem solving. In its traditional application, a fixed ASP program for a given problem is designed and the…

Artificial Intelligence · Computer Science 2016-08-08 Manuel Bichler , Michael Morak , Stefan Woltran

Solving a decision theory problem usually involves finding the actions, among a set of possible ones, which optimize the expected reward, possibly accounting for the uncertainty of the environment. In this paper, we introduce the…

Artificial Intelligence · Computer Science 2025-02-19 Damiano Azzolini , Elena Bellodi , Rafael Kiesel , Fabrizio Riguzzi

Neural-symbolic methods have demonstrated efficiency in enhancing the reasoning abilities of large language models (LLMs). However, existing methods mainly rely on syntactically mapping natural languages to complete formal languages like…

Computation and Language · Computer Science 2024-06-04 Yiming Wang , Zhuosheng Zhang , Pei Zhang , Baosong Yang , Rui Wang
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