Adaptation Using Iterated Estimations

  • Authors:
  • Göran Falkman

  • Affiliations:
  • -

  • Venue:
  • ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
  • Year:
  • 2002

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Abstract

A model for adaptation in case-based reasoning (CBR) is presented. Similarity assessment is based on the computation and the iterated estimation of structural relationships among representations, and adaptation is given as a special case of the general process.Compared to traditional approaches to adaptation within CBR, the presented model has the advantage of using a uniform declarative model for both case representation, similarity assessment and adaptation. As a consequence, adaptation knowledge can be made directly available during similarity assessment and for explanation purposes. The use of a uniform model also provides the possibility of a cbr approach to adaptation. The model is compared with other approaches to adaptation within CBR.