Abstract
This chapter describes an application of genetic engineering-based genetic algorithms as a tool for knowledge acquisition and re-use. This version of genetic algorithms is based on a model of neo-Darwinian evolution enhanced by an analysis of genetic changes, which occur during evolution, and by application of various operations that genetically engineer new organisms using the results of this analysis. The genetic analysis is carried out using various machine learning methods. This analysis yields domain-specific knowledge in a form of two hierarchies of beneficial and detrimental genetic features. These features can then be re-used when similar problems are solved using genetic algorithms. Layout planning problem is used to demonstrate the process and the results obtainable.
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© 2001 Springer-Verlag London
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Gero, J.S., Kazakov, V. (2001). Design Knowledge Acquisition and Re-use Using Genetic Engineering-based Genetic Algorithms. In: Roy, R. (eds) Industrial Knowledge Management. Springer, London. https://doi.org/10.1007/978-1-4471-0351-6_7
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DOI: https://doi.org/10.1007/978-1-4471-0351-6_7
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1075-0
Online ISBN: 978-1-4471-0351-6
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