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Evolutionary Case-Based Design

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Artificial Evolution (AE 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1829))

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Abstract

The paper provides a solution to the current problem of adaptation in case-based design. It presents a case-based model of design, using an evolutionary approach, for the adaptation of previously stored design solutions. It is argued that such a knowledge-lean methodology is more general in its applicability than conventional case-based design and that a fundamental genotype representation allows for using the case base in a variety of domain and problem situations. A prototypical example in the context of 2-D spatial design of houses is used to test the efficacy and efficiency of this approach.

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Author information

Authors and Affiliations

  1. Key Centre of Design Computing, Department of Architectural and Design Science, University of Sydney, NSW 2006, Australia

    Mike Rosenman

Authors
  1. Mike Rosenman
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Editor information

Editors and Affiliations

  1. Laboratoire d’Informatique du Littoral, Maison de la Recherche Blaise Pascal, 50 rue Ferdinand Buisson, BP 719, 62228, CALAIS Cedex, France

    Cyril Fonlupt

  2. LGI2P, EMA-EERIE, Parc Scientifique Georges Besses, F-30000, Nîmes, France

    Jin-Kao Hao

  3. INRIA Saclay - Ile-de-France, Parc Orsay Université, 4, rue Jacques Monod, 91893, ORSAY Cedex, France

    Evelyne Lutton

  4. TAO, INRIA Saclay & LRI (UMR CNRS 8623), Bât 490, Université Paris-Sud, 91405, Orsay Cedex, France

    Marc Schoenauer

  5. Centre de Mathematiques Appliquees Ecole Polytechnique, 91 128, Palaiseau, France

    Edmund Ronald

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© 2000 Springer-Verlag Berlin Heidelberg

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Rosenman, M. (2000). Evolutionary Case-Based Design. In: Fonlupt, C., Hao, JK., Lutton, E., Schoenauer, M., Ronald, E. (eds) Artificial Evolution. AE 1999. Lecture Notes in Computer Science, vol 1829. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10721187_4

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  • DOI: https://doi.org/10.1007/10721187_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67846-5

  • Online ISBN: 978-3-540-44908-9

  • eBook Packages: Springer Book Archive

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