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This paper proposes a connection method \`a la Bibel for an exception-tolerant family of description logics (DLs). As for the language, we assume the DL $\mathcal{ALCH}$ extended with two typicality operators: one on (complex) concepts and…

Logic in Computer Science · Computer Science 2023-06-23 Renan Fernandes , Fred Freitas , Ivan Varzinczak , Pedro PM Farias

This work contributes to the domains of Boolean algebra and of Bayesian probability, by proposing an algebraic extension of Boolean algebras, which implements an operator for the Bayesian conditional inference and is closed under this…

Logic · Mathematics 2011-12-19 Frederic Dambreville

Probabilistic systems are an important theme in AI domain. As the specification language, the logic PCTL is now the default logic for reasoning about probabilistic properties. In this paper, we present a natural and succinct probabilistic…

Logic in Computer Science · Computer Science 2015-05-11 Wanwei Liu , Lei Song , Ji Wang , Lijun Zhang

Recently, the description logic LE-ALC was introduced for reasoning in the semantic environment of the enriched formal contexts, and a tableaux algorithm was developed for checking the consistency of ABoxes in this logic. In this paper, we…

Logic in Computer Science · Computer Science 2025-06-09 Krishna Manoorkar , Ruoding Wang

The Semantic Web effort has steadily been gaining traction in the recent years. In particular,Web search companies are recently realizing that their products need to evolve towards having richer semantic search capabilities. Description…

Artificial Intelligence · Computer Science 2012-10-19 Thomas Lukasiewicz , Maria Vanina Martinez , Giorgio Orsi , Gerardo I. Simari

This paper presents complexity analysis and variational methods for inference in probabilistic description logics featuring Boolean operators, quantification, qualified number restrictions, nominals, inverse roles and role hierarchies.…

Artificial Intelligence · Computer Science 2012-05-14 Fabio Gagliardi Cozman , Rodrigo Bellizia Polastro

Bayesian networks provide an elegant formalism for representing and reasoning about uncertainty using probability theory. Theyare a probabilistic extension of propositional logic and, hence, inherit some of the limitations of propositional…

Artificial Intelligence · Computer Science 2007-05-23 Kristian Kersting , Luc De Raedt

We study extensions of standard description logics to the framework of polyadic modal logic. We promote a natural approach to such logics via general relation algebras that can be used to define operations on relations of all arities. As a…

Logic in Computer Science · Computer Science 2021-08-20 Jonne Iso-Tuisku , Antti Kuusisto

Although Dynamic Epistemic Logic (DEL) is an influential logical framework for representing and reasoning about information change, little is known about the computational complexity of its associated decision problems. In fact, we only…

Logic in Computer Science · Computer Science 2013-10-29 Guillaume Aucher , Francois Schwarzentruber

Modal probabilistic logics provide a framework for reasoning about probability in modal contexts, involving notions such as knowledge, belief, time, and action. In this paper, we study a particular family of these logics, extending the…

Logic in Computer Science · Computer Science 2025-12-01 Daniil Kozhemiachenko , Igor Sedlár

Whereas the semantics of probabilistic languages has been extensively studied, specification languages for their properties have received less attention -- with the notable exception of recent and on-going efforts by Joost-Pieter Katoen and…

Logic in Computer Science · Computer Science 2024-12-03 Einar Broch Johnsen , Eduard Kamburjan , Raúl Pardo , Erik Voogd , Andrzej Wąsowski

We introduce proper display calculi for intuitionistic, bi-intuitionistic and classical linear logics with exponentials, which are sound, complete, conservative, and enjoy cut-elimination and subformula property. Based on the same design,…

Logic · Mathematics 2016-11-15 Giuseppe Greco , Alessandra Palmigiano

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

The preferential conditional logic PCL, introduced by Burgess, and its extensions are studied. First, a natural semantics based on neighbourhood models, which generalise Lewis' sphere models for counterfactual logics, is proposed. Soundness…

Logic in Computer Science · Computer Science 2020-02-17 Marianna Girlando , Sara Negri , Nicola Olivetti

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

Possibilistic logic, an extension of first-order logic, deals with uncertainty that can be estimated in terms of possibility and necessity measures. Syntactically, this means that a first-order formula is equipped with a possibility degree…

Artificial Intelligence · Computer Science 2013-02-28 Bernhard Hollunder

This paper develops a declarative language, P-log, that combines logical and probabilistic arguments in its reasoning. Answer Set Prolog is used as the logical foundation, while causal Bayes nets serve as a probabilistic foundation. We give…

Artificial Intelligence · Computer Science 2008-12-04 Chitta Baral , Michael Gelfond , Nelson Rushton

Circumscription is one of the main approaches for defining non-monotonic description logics (DLs). While the decidability and complexity of traditional reasoning tasks such as satisfiability of circumscribed DL knowledge bases (KBs) is well…

Artificial Intelligence · Computer Science 2023-06-08 Carsten Lutz , Quentin Manière , Robin Nolte

The aim of this paper is to show how we can handle the Recognising Textual Entailment (RTE) task by using Description Logics (DLs). To do this, we propose a representation of natural language semantics in DLs inspired by existing…

Computation and Language · Computer Science 2007-10-17 Paul Bedaride

Influence diagrams (IDs) are well-known formalisms extending Bayesian networks to model decision situations under uncertainty. Although they are convenient as a decision theoretic tool, their knowledge representation ability is limited in…

Logic in Computer Science · Computer Science 2020-07-02 Erman Acar , Rafael Peñaloza