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Engineering Self-modeling Systems: Application to Biology

  • Conference paper
Engineering Societies in the Agents World IX (ESAW 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5485))

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Abstract

Complexity of today’s systems prevents designers from knowing everything about them and makes engineering them a difficult task for which classical engineering approaches are no longer valid. Such a challenge is especially encountered in actual complex systems simulation in which underlying computational model is very tough to design. A prospective solution is to unburden designers as much as possible by letting this computational model self-build. Adaptive multi-agent systems are the foundation of the four-layer agent model proposed here for endowing systems with the ability to self-tune, self-organize and self-assemble. This agent model has been applied to an application (MicroMega) related to computational biology which aim is to model the functional behavior of unicellular yeast Saccharomyces Cerevisiae.

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Author information

Authors and Affiliations

  1. Institut de Recherche en Informatique de Toulouse, University of Toulouse III, 118 route de Narbonne, 31062, Toulouse cedex 9, France

    Carole Bernon & Jean-Pierre Mano

  2. UPETEC, 10 avenue de l’Europe, 31520, Ramonville, France

    Davy Capera

Authors
  1. Carole Bernon
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  2. Davy Capera
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  3. Jean-Pierre Mano
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Editor information

Editors and Affiliations

  1. National Centre for Scientific Research "Demokritos", Institute of Informatics & Telecommunications, Software & Knowledge Engineering Laboratory,, 15310, Athens, Greece

    Alexander Artikis

  2. Multi-Agent Systems Department, ENS Mines Saint-Etienne, 158 Cours Fauriel, 42023, Saint-Etienne Cedex 02, France

    Gauthier Picard  & Laurent Vercouter  & 

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Bernon, C., Capera, D., Mano, JP. (2009). Engineering Self-modeling Systems: Application to Biology. In: Artikis, A., Picard, G., Vercouter, L. (eds) Engineering Societies in the Agents World IX. ESAW 2008. Lecture Notes in Computer Science(), vol 5485. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02562-4_14

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  • DOI: https://doi.org/10.1007/978-3-642-02562-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02561-7

  • Online ISBN: 978-3-642-02562-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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