A Genetic Engineering Approach to Genetic Algorithms

Authors:
John S. Gero;Vladimir S. Kazakov
Affiliations:
Key Centre of Design Computing and Cognition, Department of Architectural and Design Science, The University of Sydney, NSW 2006, Australia;Key Centre of Design Computing and Cognition, Department of Architectural and Design Science, The University of Sydney, NSW 2006, Australia
Venue:
Evolutionary Computation
Year:
2001

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Abstract

We present an extension to the standard genetic algorithm (GA), which is based on concepts of genetic engineering. The motivation is to discover useful and harmful genetic materials and then execute an evolutionary process in such a way that the population becomes increasingly composed of useful genetic material and increasingly free of the harmful genetic material. Compared to the standard GA, it provides some computational advantages as well as a tool for automatic generation of hierarchical genetic representations specifically tailored to suit certain classes of problems.