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Related papers: Reasoning in the Description Logic ALC under Categ…

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Inthispaperwedescribeaconcept-wisemulti-preferencesemantics for description logic which has its root in the preferential approach for modeling defeasible reasoning in knowledge representation. We argue that this proposal, beside satisfying…

Artificial Intelligence · Computer Science 2020-09-03 Laura Giordano , Valentina Gliozzi , Daniele Theseider Dupré

We show that the proof-theoretic notion of logical preorder coincides with the process-theoretic notion of contextual preorder for a CCS-like calculus obtained from the formula-as-process interpretation of a fragment of linear logic. The…

Logic in Computer Science · Computer Science 2019-02-20 Yuxin Deng , Iliano Cervesato , Robert J. Simmons

Argumentation has proved a useful tool in defining formal semantics for assumption-based reasoning by viewing a proof as a process in which proponents and opponents attack each others arguments by undercuts (attack to an argument's premise)…

Logic in Computer Science · Computer Science 2007-05-23 Ralf Schweimeier , Michael Schroeder

Relational descriptions have been used in formalizing diverse computational notions, including, for example, operational semantics, typing, and acceptance by non-deterministic machines. We therefore propose a (restricted) logical theory…

Logic in Computer Science · Computer Science 2010-09-02 Andrew Gacek , Dale Miller , Gopalan Nadathur

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

We encode arrays as functions which, in turn, are encoded as sets of ordered pairs. The set cardinality of each of these functions coincides with the length of the array it is representing. Then we define a fragment of set theory that is…

Logic in Computer Science · Computer Science 2026-05-12 Maximiliano Cristiá , Gianfranco Rossi

Sub-sub-intuitionistic logic is obtained from intuitionistic logic by weakening the implication and removing distributivity. It can alternatively be viewed as conditional weak positive logic. We provide semantics for sub-sub-intuitionistic…

Logic · Mathematics 2024-08-23 Jonte Deakin , Jim de Groot

Fusions are a simple way of combining logics. For normal modal logics, fusions have been investigated in detail. In particular, it is known that, under certain conditions, decidability transfers from the component logics to their fusion.…

Artificial Intelligence · Computer Science 2011-06-10 F. Baader , C. Lutz , H. Sturm , F. Wolter

Sets with atoms serve as an alternative to ZFC foundations for mathematics, where some infinite, though highly symmetric sets, behave in a finitistic way. Therefore, one can try to carry over analysis of the classical algorithms from finite…

Logic in Computer Science · Computer Science 2021-01-26 Michał R. Przybyłek

We relate two formerly independent areas: Formal concept analysis and logic of domains. We will establish a correspondene between contextual attribute logic on formal contexts resp. concept lattices and a clausal logic on coherent algebraic…

Logic in Computer Science · Computer Science 2007-05-23 Pascal Hitzler , Matthias Wendt

Answer-set programming (ASP) paradigm is a way of using logic to solve search problems. Given a search problem, to solve it one designs a theory in the logic so that models of this theory represent problem solutions. To compute a solution…

Logic in Computer Science · Computer Science 2007-05-23 Deborah East , Miroslaw Truszczynski

In this paper, we present an approach to define the semantics for object-oriented modeling languages. One important property of this semantics is to support underspecified and incomplete models. To this end, semantics is given as predicates…

Software Engineering · Computer Science 2014-09-24 Hans Grönninger , Jan Oliver Ringert , Bernhard Rumpe

We propose a method that learns a discriminative yet semantic space for object categorization, where we also embed auxiliary semantic entities such as supercategories and attributes. Contrary to prior work which only utilized them as side…

Computer Vision and Pattern Recognition · Computer Science 2014-12-10 Sung Ju Hwang , Leonid Sigal

Modal description logics feature modalities that capture dependence of knowledge on parameters such as time, place, or the information state of agents. E.g., the logic S5-ALC combines the standard description logic ALC with an S5-modality…

Logic in Computer Science · Computer Science 2017-05-24 Paul Wild , Lutz Schröder

A type theory is presented that combines (intuitionistic) linear types with type dependency, thus properly generalising both intuitionistic dependent type theory and full linear logic. A syntax and complete categorical semantics are…

Logic in Computer Science · Computer Science 2026-05-07 Matthijs Vákár

By using the abstract structures investigated in the first Part of this article, we develop a semantics for an epistemic language, which expresses sentences like "Alice knows that Bob does not understand that PI is irrational". One is…

With the rise of knowledge management and knowledge economy, the knowledge elements that directly link and embody the knowledge system have become the research focus and hotspot in certain areas. The existing knowledge element…

Logic in Computer Science · Computer Science 2019-04-17 Bin Wen , Jianhou Gan , Juan L. G. Guirao , Wei Gao

Over the past decade a considerable amount of research has been done to expand logic programming languages to handle incomplete information. One such language is the language of epistemic specifications. As is usual with logic programming…

Artificial Intelligence · Computer Science 2007-05-23 Richard Watson

Conventionally, AI models are thought to trade off explainability for lower accuracy. We develop a training strategy that not only leads to a more explainable AI system for object classification, but as a consequence, suffers no perceptible…

Computer Vision and Pattern Recognition · Computer Science 2020-03-17 Andrea Zunino , Sarah Adel Bargal , Riccardo Volpi , Mehrnoosh Sameki , Jianming Zhang , Stan Sclaroff , Vittorio Murino , Kate Saenko

Time series classification is a task of paramount importance, as this kind of data often arises in safety-critical applications. However, it is typically tackled with black-box deep learning methods, making it hard for humans to understand…

Machine Learning · Computer Science 2025-08-28 Irene Ferfoglia , Simone Silvetti , Gaia Saveri , Laura Nenzi , Luca Bortolussi
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