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.
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de Gómez Silva Garza, A., Maher, M.L. (1999). An Evolutionary Approach to Case Adaptation. In: Althoff, KD., Bergmann, R., Branting, L. (eds) Case-Based Reasoning Research and Development. ICCBR 1999. Lecture Notes in Computer Science, vol 1650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48508-2_12
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DOI: https://doi.org/10.1007/3-540-48508-2_12
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