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Contextual genetic algorithms: Evolving developmental rules

  • 3. Adaptive and Cognitive Systems
  • Conference paper
  • First Online:
Advances in Artificial Life (ECAL 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 929))

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Abstract

A genetic algorithm scheme with a stochastic genotype/phenotype relation is proposed. The mechanisms responsible for this intermediate level of uncertainty, are inspired by the biological system of RNA editing found in a variety of organisms. In biological systems, RNA editing represents a significant and potentially regulatory step in gene expression. The artificial algorithm here presented, will propose the evolution of such regulatory steps as an aid to the modeling of differentiated development of artificial organisms according to environmental, contextual, constraints. This mechanism of genetic string editing will then be utilized in the definition of a genetic algorithm scheme, with good scaling and evolutionary properties, in which phenotypes are represented by mathematical structures based on fuzzy set and evidence theories.

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Authors and Affiliations

  1. Department of Systems Science and Industrial Engineering, Watson School of Engineering and Applied Science, SUNY-Binghamton, 13902, Binghamton, NY, USA

    Luis Mateus Rocha

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  1. Luis Mateus Rocha
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Editor information

Federico Morán Alvaro Moreno Juan Julián Merelo Pablo Chacón

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© 1995 Springer-Verlag Berlin Heidelberg

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Rocha, L.M. (1995). Contextual genetic algorithms: Evolving developmental rules. In: Morán, F., Moreno, A., Merelo, J.J., Chacón, P. (eds) Advances in Artificial Life. ECAL 1995. Lecture Notes in Computer Science, vol 929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59496-5_312

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  • DOI: https://doi.org/10.1007/3-540-59496-5_312

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59496-3

  • Online ISBN: 978-3-540-49286-3

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