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Integration of inheritance in SNePS

  • Knowledge Representation
  • Conference paper
  • First Online:
Progress in Artificial Intelligence (EPIA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1323))

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Abstract

This paper presents a solution to two problems of inheritance theories in general: the confusion between classes and properties, and the inability to distinguish, just by looking at a link, if it was derived or introduced by the user. SNePS's (Semantic Network Processing System) inheritance system, the system where we developed a solution to both these problems, is a credulous mixed inheritance system where paths are built bottom-up and conflicts are solved with off-path preemption. This system is integrated in a general purpose representation system with general inference capabilities, SNePS [10,11]. Its unique features include a finer division of concepts and links, reification of links, the association of adequate justifications to all the conclusions, the representation of the assumptions raised, and the identification and adequate treatment of conflicts. All these features make it unique and an overall clearer system. Our system was specified using a direct (topological) approach (in contrast to translational approaches where information in the system is translated into an appropriate logic).

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References

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Authors and Affiliations

  1. Instituto Superior Técnico Departamento de Eng. Mecânica, Grupo de Inteligência Artificial, Av. Rovisco Pais, 1096, Lisboa, Portugal

    H. Sofia Pinto

Authors
  1. H. Sofia Pinto
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Editor information

Ernesto Coasta Amilcar Cardoso

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© 1997 Springer-Verlag Berlin Heidelberg

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Pinto, H.S. (1997). Integration of inheritance in SNePS. In: Coasta, E., Cardoso, A. (eds) Progress in Artificial Intelligence. EPIA 1997. Lecture Notes in Computer Science, vol 1323. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0023918

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  • DOI: https://doi.org/10.1007/BFb0023918

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63586-4

  • Online ISBN: 978-3-540-69605-6

  • eBook Packages: Springer Book Archive

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