
pmid: 11290285
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.
Cross-Over Studies, Phenotype, Models, Genetic, Mutation, Genetic Therapy, Genetic Engineering, Algorithms, Chromosomes
Cross-Over Studies, Phenotype, Models, Genetic, Mutation, Genetic Therapy, Genetic Engineering, Algorithms, Chromosomes
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