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International Conference on Logic for Programming Artificial Intelligence and Reasoning

LPAR 2012: Logic for Programming, Artificial Intelligence, and Reasoning pp 77–91Cite as

Forgetting for Defeasible Logic

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7180))

Abstract

The concept of forgetting has received significant interest in artificial intelligence recently. Informally, given a knowledge base, we may wish to forget about (or discard) some redundant parts (such as atoms, predicates, concepts, etc) but still preserve the consequences for certain forms of reasoning. In nonmonotonic reasoning, so far forgetting has been studied only in the context of extension based approaches, mainly answer-set programming. In this paper forgetting is studied in the context of defeasible logic, which is a simple, efficient and sceptical nonmonotonic reasoning approach.

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Author information

Authors and Affiliations

  1. FORTH-ICS, Greece

    Grigoris Antoniou

  2. University of Huddersfield, UK

    Grigoris Antoniou

  3. Institut für Informationssysteme, Technische Universität Wien, Austria

    Thomas Eiter

  4. School of Information and Communication Technology, Griffith University, Australia

    Kewen Wang

Authors
  1. Grigoris Antoniou
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  2. Thomas Eiter
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  3. Kewen Wang
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Editor information

Editors and Affiliations

  1. Microsoft Research, One Microsoft Way, 98052-6399, Redmond, WA, USA

    Nikolaj Bjørner

  2. School of computer Science, University of Manchester, Kilburn Building, Oxford Road, MP13 9PL, Manchester, UK

    Andrei Voronkov

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Antoniou, G., Eiter, T., Wang, K. (2012). Forgetting for Defeasible Logic. In: Bjørner, N., Voronkov, A. (eds) Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2012. Lecture Notes in Computer Science, vol 7180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28717-6_9

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  • DOI: https://doi.org/10.1007/978-3-642-28717-6_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28716-9

  • Online ISBN: 978-3-642-28717-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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