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On Supporting Strong and Default Negation in Answer-Set Program Updates

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Book cover Advances in Artificial Intelligence -- IBERAMIA 2014 (IBERAMIA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8864))

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Abstract

Existing semantics for answer-set program updates fall into two categories: either they consider only strong negation in heads of rules, or they primarily rely on default negation in heads of rules and optionally provide support for strong negation by means of a syntactic transformation.

In this paper we pinpoint the limitations of both these approaches and argue that both types of negation should be first-class citizens in the context of updates. We identify principles that plausibly constrain their interaction but are not simultaneously satisfied by any existing rule update semantics. Then we extend one of the most advanced semantics with direct support for strong negation and show that it satisfies the outlined principles as well as a variety of other desirable properties.

J. Leite and M. Slota were partially supported by FCT under project PTDC/EIA-CCO/121823/2010. The collaboration between the co-authors resulted from the Slovak–Portuguese bilateral project supported by APVV agency under SK-PT-0028-10 and by FCT under FCT/2487/3/6/2011/S.

A preliminary version of this paper appeared as [1]. An extended version of this paper with all the proofs is available at http://arxiv.org/abs/1404.6784

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Authors and Affiliations

  1. CENTRIA and Departamento de Informática, Universidade Nova de Lisboa, Lisbon, Portugal

    Martin Slota & João Leite

  2. Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia

    Martin Baláž

Authors
  1. Martin Slota
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  2. Martin Baláž
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  3. João Leite
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Correspondence to João Leite .

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Editors and Affiliations

  1. Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

    Ana L.C. Bazzan

  2. Pontifica Universidad Católica (PUC), Santiago de Chile, Chile

    Karim Pichara

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Slota, M., Baláž, M., Leite, J. (2014). On Supporting Strong and Default Negation in Answer-Set Program Updates. In: Bazzan, A., Pichara, K. (eds) Advances in Artificial Intelligence -- IBERAMIA 2014. IBERAMIA 2014. Lecture Notes in Computer Science(), vol 8864. Springer, Cham. https://doi.org/10.1007/978-3-319-12027-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-12027-0_4

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  • Print ISBN: 978-3-319-12026-3

  • Online ISBN: 978-3-319-12027-0

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