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We address the problem of compiling defeasible theories to Datalog$^\neg$ programs. We prove the correctness of this compilation, for the defeasible logic $DL(\partial_{||})$, but the techniques we use apply to many other defeasible logics.…

Logic in Computer Science · Computer Science 2024-08-28 Michael J. Maher

The class of defeasible logics is only vaguely defined -- it is defined by a few exemplars and the general idea of efficient reasoning with defeasible rules. The recent definition of the defeasible logic $DL(\partial_{||})$ introduced new…

Logic in Computer Science · Computer Science 2024-05-30 Michael J. Maher

The use of meta-rules in logic, i.e., rules whose content includes other rules, has recently gained attention in the setting of non-monotonic reasoning: a first logical formalisation and efficient algorithms to compute the (meta)-extensions…

Artificial Intelligence · Computer Science 2022-09-27 Francesco Olivieri , Guido Governatori , Matteo Cristani , Antonino Rotolo , Abdul Sattar

The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules…

Artificial Intelligence · Computer Science 2007-05-23 Alejandro Javier Garcia , Guillermo Ricardo Simari

Recent technological advances have led to unprecedented amounts of generated data that originate from the Web, sensor networks and social media. Analytics in terms of defeasible reasoning - for example for decision making - could provide…

Logic in Computer Science · Computer Science 2021-02-16 Michael J. Maher , Ilias Tachmazidis , Grigoris Antoniou , Stephen Wade , Long Cheng

Linear Logic and Defeasible Logic have been adopted to formalise different features of knowledge representation: consumption of resources, and non monotonic reasoning in particular to represent exceptions. Recently, a framework to combine…

Artificial Intelligence · Computer Science 2019-08-19 Francesco Olivieri , Guido Governatori , Claudio Tomazzoli , Matteo Cristani

Defeasible logics provide several linguistic features to support the expression of defeasible knowledge. There is also a wide variety of such logics, expressing different intuitions about defeasible reasoning. However, the logics can only…

Logic in Computer Science · Computer Science 2021-02-16 Guido Governatori , Michael J. Maher

Differentiable logics (DL) have recently been proposed as a method of training neural networks to satisfy logical specifications. A DL consists of a syntax in which specifications are stated and an interpretation function that translates…

Logic in Computer Science · Computer Science 2023-10-06 Natalia Ślusarz , Ekaterina Komendantskaya , Matthew L. Daggitt , Robert Stewart , Kathrin Stark

We extend description logics (DLs) with non-monotonic reasoning features. We start by investigating a notion of defeasible subsumption in the spirit of defeasible conditionals as studied by Kraus, Lehmann and Magidor in the propositional…

Artificial Intelligence · Computer Science 2019-04-17 Katarina Britz , Giovanni Casini , Thomas Meyer , Kody Moodley , Uli Sattler , Ivan Varzinczak

DL^N is a recent approach that extends description logics with defeasible reasoning capabilities. In this paper we provide an overview on DL^N, illustrating the underlying knowledge engineering requirements as well as the characteristic…

Artificial Intelligence · Computer Science 2020-09-18 Piero A. Bonatti , Iliana M. Petrova , Luigi Sauro

The importance of transformations and normal forms in logic programming, and generally in computer science, is well documented. This paper investigates transformations and normal forms in the context of Defeasible Logic, a simple but…

Logic in Computer Science · Computer Science 2021-02-16 G. Antoniou , D. Billington , G. Governatori , M. J. Maher

Defeasible argumentation has experienced a considerable growth in AI in the last decade. Theoretical results have been combined with development of practical applications in AI & Law, Case-Based Reasoning and various knowledge-based…

Artificial Intelligence · Computer Science 2016-08-16 Carlos Iván Chesñevar , Guillermo Ricardo Simari , Alejandro Javier García

Defeasible reasoning is a simple but efficient approach to nonmonotonic reasoning that has recently attracted considerable interest and that has found various applications. Defeasible logic and its variants are an important family of…

Logic in Computer Science · Computer Science 2012-06-26 Grigoris Antoniou , David Billington , Guido Governatori , Michael J. Maher

Large Language Models (LLMs) have gained prominence in the AI landscape due to their exceptional performance. Thus, it is essential to gain a better understanding of their capabilities and limitations, among others in terms of nonmonotonic…

Artificial Intelligence · Computer Science 2024-10-17 Ilias Tachmazidis , Sotiris Batsakis , Grigoris Antoniou

In the last years, there has been an increasing demand of a variety of logical systems, prompted mostly by applications of logic in AI and other related areas. Labeled Deductive Systems (LDS) were developed as a flexible methodology to…

Artificial Intelligence · Computer Science 2007-05-23 Carlos Iván Chesñevar , Guillermo Ricardo Simari

Defeasible logic is a rule-based nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts…

Artificial Intelligence · Computer Science 2009-09-29 Michael J. Maher

Plausible reasoning concerns situations whose inherent lack of precision is not quantified; that is, there are no degrees or levels of precision, and hence no use of numbers like probabilities. A hopefully comprehensive set of principles…

Artificial Intelligence · Computer Science 2017-04-05 David Billington

Linear Logic and Defeasible Logic have been adopted to formalise different features relevant to agents: consumption of resources, and reasoning with exceptions. We propose a framework to combine sub-structural features, corresponding to the…

Artificial Intelligence · Computer Science 2018-09-12 Francesco Olivieri , Guido Governatori , Matteo Cristani , Nick van Beest , Silvano Colombo-Tosatto

The KLM approach to defeasible reasoning introduces a weakened form of implication into classical logic. This allows one to incorporate exceptions to general rules into a logical system, and for old conclusions to be withdrawn upon learning…

Artificial Intelligence · Computer Science 2024-10-08 Nicholas Leisegang , Thomas Meyer , Sebastian Rudolph

We provide a method of translating theories of Nute's defeasible logic into logic programs, and a corresponding translation in the opposite direction. Under certain natural restrictions, the conclusions of defeasible theories under the…

Artificial Intelligence · Computer Science 2011-06-13 Frederick Maier
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