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Related papers: Axiomatic Aspects of Default Inference

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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

Different types of reasoning impose different structural demands on representational systems, yet no systematic account of these demands exists across psychology, AI, and philosophy of mind. I propose a framework identifying four structural…

Artificial Intelligence · Computer Science 2026-04-03 Yiling Wu

In this paper we prove that no consistent finitely axiomatized theory one-dimensionally interprets its own extension with predicative comprehension. This constitutes a result with the flavor of the Second Incompleteness Theorem whose…

Logic · Mathematics 2021-09-07 Fedor Pakhomov , Albert Visser

We endow prioritised default logic (PDL) with argumentation semantics using the ASPIC+ framework for structured argumentation, and prove that the conclusions of the justified arguments are exactly the prioritised default extensions.…

Artificial Intelligence · Computer Science 2015-07-02 Anthony P. Young , Sanjay Modgil , Odinaldo Rodrigues

This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argumentative-consequence relation taking into account the existence of consistent arguments in favor of a conclusion and the…

Artificial Intelligence · Computer Science 2013-03-08 Salem Benferhat , Didier Dubois , Henri Prade

Linear Response theory aims to predict how added forcing alters the statistical properties of an unforced system. These kinds of questions have been studied predominantly for autonomous dynamical systems, yet many systems in the physical,…

Dynamical Systems · Mathematics 2026-04-07 Stefano Galatolo , Valerio Lucarini

We introduce and investigate a family of consequence relations with the goal of capturing certain important patterns of data-driven inference. The inspiring idea for our framework is the fact that data may reject, possibly to some degree,…

Logic · Mathematics 2024-08-23 Paolo Baldi , Esther Anna Corsi , Hykel Hosni

A default theory can be characterized by its sets of plausible conclusions, called its extensions. But, due to the theoretical complexity of Default Logic (Sigma_2p-complete), the problem of finding such an extension is very difficult if…

Artificial Intelligence · Computer Science 2007-05-23 P. Nicolas , F. Saubion , I. Stephan

In this paper an approach to automated deduction under uncertainty,based on possibilistic logic, is proposed ; for that purpose we deal with clauses weighted by a degree which is a lower bound of a necessity or a possibility measure,…

Artificial Intelligence · Computer Science 2013-04-08 Didier Dubois , Jerome Lang , Henri Prade

This paper studies how violations of structural assumptions like expected utility and exponential discounting can be connected to basic rationality violations, even though these assumptions are typically regarded as independent building…

Theoretical Economics · Economics 2024-02-20 Xi Zhi Lim

We study here preference revision, considering both the monotonic case where the original preferences are preserved and the nonmonotonic case where the new preferences may override the original ones. We use a relational framework in which…

Databases · Computer Science 2007-05-23 Jan Chomicki , Joyce Song

A number of writers(Joseph Halpern and Fahiem Bacchus among them) have offered semantics for formal languages in which inferences concerning probabilities can be made. Our concern is different. This paper provides a formalization of…

Artificial Intelligence · Computer Science 2013-03-25 Henry E. Kyburg

In this paper, we address the problem of change in an abstract argumentation system. We focus on a particular change: the addition of a new argument which interacts with previous arguments. We study the impact of such an addition on the…

Artificial Intelligence · Computer Science 2014-01-17 Claudette Cayrol , Florence Dupin de Saint-Cyr , Marie-Christine Lagasquie-Schiex

The semantic web is an open and distributed environment in which it is hard to guarantee consistency of knowledge and information. Under the standard two-valued semantics everything is entailed if knowledge and information is inconsistent.…

Artificial Intelligence · Computer Science 2014-05-01 Wenzhao Qiao , Nico Roos

We investigate non-wellfounded proof systems based on parsimonious logic, a weaker variant of linear logic where the exponential modality ! is interpreted as a constructor for streams over finite data. Logical consistency is maintained at a…

Logic in Computer Science · Computer Science 2025-09-03 Matteo Acclavio , Gianluca Curzi , Giulio Guerrieri

In the present paper, the existence and multiplicity problems of extensions are addressed. The focus is on extension of the stable type. The main result of the paper is an elegant characterization of the existence and multiplicity of…

Artificial Intelligence · Computer Science 2007-05-23 Bart Verheij

I deal with two approaches to proof-theoretic semantics: one based on argument structures and justifications, which I call reducibility semantics, and one based on consequence among (sets of) formulas over atomic bases, called base…

Logic · Mathematics 2025-11-11 Antonio Piccolomini d'Aragona

We introduce the operation of possibility qualification and show how. this modal-like operator can be used to represent "typical" or default knowledge in a theory of nonmonotonic reasoning. We investigate the representational power of this…

Artificial Intelligence · Computer Science 2013-04-10 Ronald R. Yager

The paper introduces a basic logic of knowledge and abduction by extending Levesque logic of only-knowing with an abduction modal operator defined via the combination of basic epistemic concepts. The upshot is an alternative approach to…

Artificial Intelligence · Computer Science 2026-01-09 Sanderson Molick , Vaishak Belle

Ontologies formalise how the concepts from a given domain are interrelated. Despite their clear potential as a backbone for explainable AI, existing ontologies tend to be highly incomplete, which acts as a significant barrier to their more…

Artificial Intelligence · Computer Science 2021-05-12 Steven Schockaert , Yazmín Ibáñez-García , Víctor Gutiérrez-Basulto