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Demonstrating the Evolution of Complex Genetic Representations: An Evolution of Artificial Plants

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Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2723))

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Abstract

A common idea is that complex evolutionary adaptation is enabled by complex genetic representations of phenotypic traits. This paper demonstrates how, according to a recently developed theory, genetic representations can self-adapt in favor of evolvability, i.e., the chance of adaptive mutations. The key for the adaptability of genetic representations is neutrality inherent in non-trivial genotype-phenotype mappings and neutral mutations that allow for transitions between genetic representations of the same phenotype. We model an evolution of artificial plants, encoded by grammar-like genotypes, to demonstrate this theory.

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Author information

Authors and Affiliations

  1. Institut für Neuroinformatik, Ruhr-Universität Bochum ND-04, 44780, Bochum, Germany

    Marc Toussaint (Chair for Theoretical Biology)

Authors
  1. Marc Toussaint
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Editor information

Editors and Affiliations

  1. Lawrence Livermore National Laboratory, Center for Applied Scientific Computing (CASC), 7000 East Avenue, L-561, Livermore, CA, 94550, USA

    Erick Cantú-Paz

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Toussaint, M. (2003). Demonstrating the Evolution of Complex Genetic Representations: An Evolution of Artificial Plants. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45105-6_8

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  • DOI: https://doi.org/10.1007/3-540-45105-6_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40602-0

  • Online ISBN: 978-3-540-45105-1

  • eBook Packages: Springer Book Archive

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