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An Evolutionary Approach to Case Adaptation

  • Andrés de Gómez Silva Garza
  • Mary Lou Maher
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1650)

Abstract

We present a case adaptation method that employs ideas from the field of genetic algorithms. Two types of adaptations, case combination and case mutation, are used to evolve variations on the contents of retrieved cases until a satisfactory solution is found for a new specified problem. A solution is satisfactory if it matches the specified requirements and does not violate any constraints imposed by the domain of applicability. We have implemented our ideas in a computational system called GENCAD, applied to the layout design of residences such that they conform to the principles of feng shui, the Chinese art of placement. This implementation allows us to evaluate the use of GA’s for case adaptation in CBR. Experimental results show the role of representation and constraints.

Keywords

Genetic Algorithm Evolutionary Approach Case Adaptation Layout Design House Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Andrés de Gómez Silva Garza
    • 1
  • Mary Lou Maher
    • 1
  1. 1.Key Centre of Design Computing Department of Architectural and Design ScienceUniversity of SydneyAustralia

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