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Dynamic Knowledge Representation and Its Applications

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Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 2000)

Abstract

This paper has two main objectives. One is to show that the dynamic knowledge representation paradigm introduced in [ALP+00] and the associated language LUPS, defined in [APPP 99], constitute na- tural, powerful and expressive tools for representing dynamically changing knowledge. We do so by demonstrating the applicability of the dynamic knowledge representation paradigm and the language LUPS to several broad knowledge representation domains, for each of which we provide an illustrative example.

Our second objective is to extend our approach to allow proper handling of conflicting updates. So far, our research on knowledge updates was restricted to a two-valued semantics, which, in the presence of conflict- ing updates, leads to an inconsistent update, even though the updated knowledge base does not necessarily contain any truly contradictory in- formation. By extending our approach to the three-valued semantics we gain the added expressiveness allowing us to express undefined or non- committal updates.

This work was partially supported by PRAXIS XXI project MENTAL, and a NATO scholarship while L. M. Pereira was on leave at the Department of Computer Science, University of California, Riverside. We thank João Leite for helpful discussions.

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Alferes, J.J., Pereira, L.M., Przymusinska, H., Przymusinski, T.C., Quaresma, P. (2000). Dynamic Knowledge Representation and Its Applications. In: Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2000. Lecture Notes in Computer Science, vol 1904. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45331-8_1

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  • DOI: https://doi.org/10.1007/3-540-45331-8_1

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  • Print ISBN: 978-3-540-41044-7

  • Online ISBN: 978-3-540-45331-4

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