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Labelled Deduction

  • Book
  • © 2000

Overview

Part of the book series: Applied Logic Series (APLS, volume 17)

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Table of contents (10 chapters)

Keywords

About this book

Labelled deduction is an approach to providing frameworks for presenting and using different logics in a uniform and natural way by enriching the language of a logic with additional information of a semantic proof-theoretical nature.
Labelled deduction systems often possess attractive properties, such as modularity in the way that families of related logics are presented, parameterised proofs of metatheoretic properties, and ease of mechanisability. It is thus not surprising that labelled deduction has been applied to problems in computer science, AI, mathematical logic, cognitive science, philosophy and computational linguistics - for example, formalizing and reasoning about dynamic `state oriented' properties such as knowledge, belief, time, space, and resources.

Editors and Affiliations

  • Albert-Ludwigs-Universität Freiburg, Germany

    David Basin, Luca Viganò

  • Università di Ferrara, Italy

    Marcello D’Agostino

  • Department of Computer Science, King’s College, London, UK

    Dov M. Gabbay

  • Logical GmbH, Frankfurt am Main, Germany

    Seán Matthews

About the editors

Luca Viganò is an assistant professor at the Institute for Computer Science of the University of Freiburg (Germany). His research focuses on the theory and applications of non-classical logics, of proof development systems, of logical frameworks, and of logics for security.

Bibliographic Information

  • Book Title: Labelled Deduction

  • Editors: David Basin, Marcello D’Agostino, Dov M. Gabbay, Seán Matthews, Luca Viganò

  • Series Title: Applied Logic Series

  • DOI: https://doi.org/10.1007/978-94-011-4040-9

  • Publisher: Springer Dordrecht

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media Dordrecht 2000

  • Hardcover ISBN: 978-0-7923-6237-1Published: 30 April 2000

  • Softcover ISBN: 978-94-010-5781-3Published: 08 October 2012

  • eBook ISBN: 978-94-011-4040-9Published: 06 December 2012

  • Series ISSN: 1386-2790

  • Edition Number: 1

  • Number of Pages: XI, 267

  • Topics: Logic, Artificial Intelligence

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