1992
DOI: 10.7551/mitpress/1090.001.0001
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Adaptation in Natural and Artificial Systems

Abstract: Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications. In its most familiar form, adaptation is a biological process, w… Show more

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Cited by 14,818 publications
(10,985 citation statements)
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“…The compact 3D-QSAR models are actually generated in the Seventh Step as part of model building, optimization, comparison, and evaluation using a genetic algorithm, GA [11]. The specific genetic algorithm currently used in the 4D-QSAR program [5] is the genetic function approximation, GFA [12,13].…”
Section: Methodsmentioning
confidence: 99%
“…The compact 3D-QSAR models are actually generated in the Seventh Step as part of model building, optimization, comparison, and evaluation using a genetic algorithm, GA [11]. The specific genetic algorithm currently used in the 4D-QSAR program [5] is the genetic function approximation, GFA [12,13].…”
Section: Methodsmentioning
confidence: 99%
“…The GA is an intelligent search mechanism able to learn which regions of the search space represent good solutions through the concept of schemata. [9] The use of GAs for optimising cluster geometries was pioneered by Hartke [6, 7, 12±15] and Xiao and Williams. [16] Other milestones in the development of cluster GAs are due to Zeiri, [17±19] who introduced a GA that operated on the real-valued Cartesian coordinates of the clusters rather than binary-encoded coordinates, and to Deaven and Ho, [20,21] who performed a gradient-driven local minimisation of the cluster energy after each new cluster was generated.…”
Section: Genetic Algorithmsmentioning
confidence: 99%
“…GA is a search technique developed by Holland, 19 that mimics the process of natural selection and natural genetics. In this algorithm, a set of decision variables are first coded in the form of a set of randomly generated binary numbers (0 and 1), called strings or chromosomes, thereby creating a "population (gene pool)" of such binary strings.…”
Section: Appendix 1: a Note On Genetic Algorithm 19 -21mentioning
confidence: 99%