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A numerical strategy to defectuous knowledge using

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Abstract

Knowledge-Based Systems are based on an often defectuous knowledge, be this knowledge acquired from experts or learned from examples.

This paper presents a strategy designed to cope with defectuous knowledge: given a set of rules, it builds a similarity function over the work space of the problem. This similarity function together with a set of examples then enables case-based reasoning, through aK-nearest-neighbour-like process.

Compared to other case-based reasoning techniques, the advantage of this approach is the following: the “topology” of the space is automatically induced from the given rules, instead of being explicitly provided (and tuned) by the expert.

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Authors and Affiliations

  1. LMS-CNRS URA 317, Ecole Polytechnique, F-91128, Palaiseau, France

    Michèle Sebag

  2. CMAP-CNRS URA 756, Ecole Polytechnique, F-91128, Palaiseau, France

    Marc Schoenauer

Authors
  1. Michèle Sebag
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  2. Marc Schoenauer
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Sebag, M., Schoenauer, M. A numerical strategy to defectuous knowledge using. Ann Oper Res 55, 379–401 (1995). https://doi.org/10.1007/BF02030868

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