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Stereotypical reasoning assumes that the situation at hand is one of a kind and that it enjoys the properties generally associated with that kind of situation. It is one of the most basic forms of nonmonotonic reasoning. A formal model for…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann

We revisit the issue of connections between two leading formalisms in nonmonotonic reasoning: autoepistemic logic and default logic. For each logic we develop a comprehensive semantic framework based on the notion of a belief pair. The set…

Artificial Intelligence · Computer Science 2007-05-23 Marc Denecker , Victor W. Marek , Miroslaw Truszczynski

We define a family of intuitionistic non-normal modal logics; they can bee seen as intuitionistic counterparts of classical ones. We first consider monomodal logics, which contain only one between Necessity and Possibility. We then consider…

Logic in Computer Science · Computer Science 2019-01-30 Tiziano Dalmonte , Charles Grellois , Nicola Olivetti

Ontology is a popular method for knowledge representation in different domains, including the legal domain, and description logics (DL) is commonly used as its description language. To handle reasoning based on inconsistent DL-based legal…

Artificial Intelligence · Computer Science 2022-09-20 Zhe Yu , Yiwei Lu

This paper considers KLM-style preferential non-monotonic reasoning in the setting of propositional team semantics. We show that team-based propositional logics naturally give rise to cumulative non-monotonic entailment relations. Motivated…

Artificial Intelligence · Computer Science 2024-05-14 Kai Sauerwald , Juha Kontinen

Default logic encounters some conceptual difficulties in representing common sense reasoning tasks. We argue that we should not try to formulate modular default rules that are presumed to work in all or most circumstances. We need to take…

Artificial Intelligence · Computer Science 2013-02-08 Choh Man Teng

This paper continues an established line of research about the relations between argumentation theory, particularly assumption-based argumentation, and different kinds of logic programs. In particular, we extend known result of Caminada,…

Artificial Intelligence · Computer Science 2025-07-09 Jesse Heyninck , Ofer Arieli

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

We extend the $ASPIC^+$ framework for structured argumentation so as to allow applications of the reasoning by cases inference scheme for defeasible arguments. Given an argument with conclusion `$A$ or $B$', an argument based on $A$ with…

Artificial Intelligence · Computer Science 2017-03-27 Mathieu Beirlaen , Jesse Heyninck , Christian Straßer

Over the past few decades, non-monotonic reasoning has developed to be one of the most important topics in computational logic and artificial intelligence. Different ways to introduce non-monotonic aspects to classical logic have been…

Computational Complexity · Computer Science 2010-09-13 Michael Thomas , Heribert Vollmer

We investigate properties of ABA+, a formalism that extends the well studied structured argumentation formalism Assumption-Based Argumentation (ABA) with a preference handling mechanism. In particular, we establish desirable properties that…

Artificial Intelligence · Computer Science 2017-11-07 Kristijonas Cyras , Francesca Toni

In ASPIC-style structured argumentation an argument can rebut another argument by attacking its conclusion. Two ways of formalizing rebuttal have been proposed: In restricted rebuttal, the attacked conclusion must have been arrived at with…

Artificial Intelligence · Computer Science 2020-07-10 Marcos Cramer , Meghna Bhadra

We propose a novel approach to logic-based learning which generates assumption-based argumentation (ABA) frameworks from positive and negative examples, using a given background knowledge. These ABA frameworks can be mapped onto logic…

Artificial Intelligence · Computer Science 2023-05-26 Maurizio Proietti , Francesca Toni

Nonmonotonic reasoning is a pattern of reasoning that allows an agent to make and retract (tentative) conclusions from inconclusive evidence. This paper gives a possible-worlds interpretation of the nonmonotonic reasoning problem based on…

Artificial Intelligence · Computer Science 2013-04-10 Carl Kadie

To resolve conflicts among norms, various nonmonotonic formalisms can be used to perform prioritized normative reasoning. Meanwhile, formal argumentation provides a way to represent nonmonotonic logics. In this paper, we propose a…

Artificial Intelligence · Computer Science 2018-03-06 Beishui Liao , Nir Oren , Leendert van der Torre , Serena Villata

In order to enrich dynamic semantic theories with a `pragmatic' capacity, we combine dynamic and nonmonotonic (preferential) logics in a modal logic setting. We extend a fragment of Van Benthem and De Rijke's dynamic modal logic with…

cmp-lg · Computer Science 2008-02-03 Jan Jaspars , Megumi Kameyama

Modal dependence logics are modal logics defined on the basis of team semantics and have the downward closure property. In this paper, we introduce sound and complete deduction systems for the major modal dependence logics, especially those…

Logic · Mathematics 2018-12-19 Fan Yang

Assumption-based Argumentation (ABA) is advocated as a unifying formalism for various forms of non-monotonic reasoning, including logic programming. It allows capturing defeasible knowledge, subject to argumentative debate. While, in much…

Artificial Intelligence · Computer Science 2024-11-11 Emanuele De Angelis , Maurizio Proietti , Francesca Toni

Modelling qualitative uncertainty in formal argumentation is essential both for practical applications and theoretical understanding. Yet, most of the existing works focus on \textit{abstract} models for arguing with uncertainty. Following…

Artificial Intelligence · Computer Science 2026-02-18 Carlo Proietti , Antonio Yuste-Ginel

We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility…

Artificial Intelligence · Computer Science 2016-08-31 Nir Friedman , Joseph Y. Halpern