Abstract
Evolutionary computing is a transdisciplinary research field that centers on the emulation or simulation of natural evolution processes which in turn might be used as tools for designing and implementing artificial systems which are capable of interacting with and adapting to changing task environments. Our motivation to enter into the field of evolutionary computing (EC) is based on formal and methodological grounds. Formally, because we are interested in the algorithmic compression of EC techniques, thereby focusing our interest on minimal difference machines, called autogenetic algorithms (AGAs). Methodologically, because EC offers new ways to multivariate search in complex features spaces. The present EC approach differs in many respects from currently traded EC techniques such as genetic algorithms ([HOL92]), evolution strategies ([REC94], [SCH95]), or evolution programs in general ([MIC92]), but the basic structure as displayed in figure 9.1 is maintained for reasons of comparability.
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© 1999 Springer-Verlag Berlin Heidelberg
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Zaus, M. (1999). Foundations of Evolutionary Computing. In: Crisp and Soft Computing with Hypercubical Calculus. Studies in Fuzziness and Soft Computing, vol 27. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1879-6_9
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DOI: https://doi.org/10.1007/978-3-7908-1879-6_9
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-662-11380-6
Online ISBN: 978-3-7908-1879-6
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