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Knowledge Representation Using High-Level Non-monotonic Reasoning

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MICAI 2000: Advances in Artificial Intelligence (MICAI 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1793))

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Abstract

We introduce the new paradigm of High-Level Non-Monotonic reasoning (HLNM). This paradigm is the consolidation of our recent results on disjunctions, sets, explicit and implicit negation, and partial-order clauses. We show how these concepts are integrated in a natural way into the standard logic programming framework. For this purpose, we present several well known examples from the literature that motivate the need of this new paradigm. Finally, we define a declarative semantics for HLNM reasoning.

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Author information

Authors and Affiliations

  1. Departamento de Ingenieria en Sistemas Computacionales, Universidad de las Americas, Sta. Catarina Martir, Cholula, 72820, Puebla, Mexico

    Mauricio Osorio & Juan Carlos Nieves

  2. Facultad de ciencias de la computación, Benemerita Universidad Autonoma de Puebla, 75570, Puebla, Mexico

    Fernando Zacarias

  3. Departamento de Ingenieria y Ciencias Atizapan de Zaragoza, Edo. de, Instituto Tecnológico y de Estudios Superiores de Monterrey, CEM, Mexico

    Erika Saucedo

Authors
  1. Mauricio Osorio
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  2. Juan Carlos Nieves
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  3. Fernando Zacarias
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  4. Erika Saucedo
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Editor information

Editors and Affiliations

  1. Department of Computer Science Instituto Tecnológico Autónomo de México (ITAM), Río Hondo 1, 01080, México DF, México

    Osvaldo Cairó

  2. Monterrey Institute of Technology (ITESM), Campus Morelos, Av. Reforma 182-A, Lomas de Cuernvaca, Temixco, 62589, Morelos, Mexico

    L. Enrique Sucar

  3. ITESM Campus Monterrey, Research and Graduate Studies Office, Monterrey, N.L., México

    Francisco J. Cantu

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© 2000 Springer-Verlag Berlin Heidelberg

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Osorio, M., Nieves, J.C., Zacarias, F., Saucedo, E. (2000). Knowledge Representation Using High-Level Non-monotonic Reasoning. In: Cairó, O., Sucar, L.E., Cantu, F.J. (eds) MICAI 2000: Advances in Artificial Intelligence. MICAI 2000. Lecture Notes in Computer Science(), vol 1793. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10720076_2

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  • DOI: https://doi.org/10.1007/10720076_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67354-5

  • Online ISBN: 978-3-540-45562-2

  • eBook Packages: Springer Book Archive

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