A Genetic Engineering Approach to Genetic Algorithms

Autor:	Vladimir S. Kazakov, John S. Gero
Rok vydání:	2001
Předmět:	Cross-Over Studies Meta-optimization Models Genetic Cultural algorithm business.industry Computer science Quality control and genetic algorithms Genetic programming Interactive evolutionary computation Genetic Therapy Genetic operator Chromosomes Computational Mathematics Phenotype Mutation Genetic algorithm Artificial intelligence Genetic representation Genetic Engineering business Algorithms
Zdroj:	Evolutionary Computation. 9:71-92
ISSN:	1530-9304 1063-6560
DOI:	10.1162/10636560151075121
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38c080f86c8e9c3ccb815c6ebade7e81 https://doi.org/10.1162/10636560151075121 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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