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Part of the book series: Genetic Algorithms and Evolutionary Computation ((GENA,volume 8))

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Abstract

In this chapter, we define the strategies and fitness environments to be analyzed in the remainder of this work. It serves the purpose of introducing basic definitions and terminology, and of preparing the reader for the analyses presented in the following chapters. We do not attempt to introduce evolution strategies in their full generality, but rather restrict ourselves to real-valued search spaces with fitness functions f: ℝN and to \( ({\mu \mathord{\left/ {\vphantom {\mu {\rho \mathop + \limits_, \lambda }}} \right. \kern-\nulldelimiterspace} {\rho \mathop + \limits_, \lambda }}) - ES \) with intermediate recombination and with isotropic normal mutations. This choice of strategy is motivated both by that is relatively amenable to mathematical analysis and by its pervasiveness in the literature. References to other strategy variants are included where appropriate.

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© 2002 Springer Science+Business Media New York

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Arnold, D.V. (2002). Preliminaries. In: Noisy Optimization With Evolution Strategies. Genetic Algorithms and Evolutionary Computation, vol 8. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1105-2_2

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  • DOI: https://doi.org/10.1007/978-1-4615-1105-2_2

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-5397-3

  • Online ISBN: 978-1-4615-1105-2

  • eBook Packages: Springer Book Archive

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