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An artificial life approach for the synthesis of autonomous agents

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Artificial Evolution (AE 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1063))

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Abstract

This paper describes an evolutionary process producing dynamical neural networks used as “brains” for autonomous agents. The main concepts used: genetic algorithms, morphogenesis process, artificial neural networks and artificial metabolism, illustrate our conviction that some fundamental principles of nature may help to design processes from which emerge artificial autonomous agents. The evolutionary process presented here is applied to a simulated autonomous robot. The resulting neural networks are then embedded on a real mobile robot. We emphasize the role of the artificial metabolism and the role of the environment which appear to be the motors of evolution. The first results observed are encouraging and motivate a deeper investigation of this research area.

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References

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Author information

Authors and Affiliations

  1. Laboratoire I3S-CNRS, University of Nice-Sophia Antipolis, bât. 4 250, av. A. Einstein, 06560, Valbonne, France

    Olivier Michel

Authors
  1. Olivier Michel
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Editor information

Jean-Marc Alliot Evelyne Lutton Edmund Ronald Marc Schoenauer Dominique Snyers

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© 1996 Springer-Verlag Berlin Heidelberg

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Michel, O. (1996). An artificial life approach for the synthesis of autonomous agents. In: Alliot, JM., Lutton, E., Ronald, E., Schoenauer, M., Snyers, D. (eds) Artificial Evolution. AE 1995. Lecture Notes in Computer Science, vol 1063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61108-8_40

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  • DOI: https://doi.org/10.1007/3-540-61108-8_40

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61108-0

  • Online ISBN: 978-3-540-49948-0

  • eBook Packages: Springer Book Archive

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