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

  • Marc Toussaint
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2723)

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.

Keywords

Type Mutation Phenotypic Variability Direct Encode Search Distribution Organism State 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Marc Toussaint
    • 1
  1. 1.Institut für NeuroinformatikRuhr-Universität Bochum ND-04BochumGermany

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