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Evolving Specific Network Statistical Properties using a Gene Regulatory Network Model

Miguel Nicolau 1, 2, * Marc Schoenauer 1, 2 
* Corresponding author
2 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : The generation of network topologies with specific, user-specified statistical properties is the aim of this paper. This is achieved through the use of an artifical Gene Regulatory Network Model, shown previously to be able to correctly seed the population of an evolutionary algorithm, with the aim of steering the evolution towards the desired topologies. This method had previously been shown to be able to evolve scale-free topologies; the results obtained in this paper reinforce the applicability of the method, showing that the evolution of small-world topologies is also possible.
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Submitted on : Thursday, October 9, 2008 - 2:33:29 PM
Last modification on : Tuesday, October 25, 2022 - 4:16:59 PM
Long-term archiving on: : Friday, June 4, 2010 - 12:24:54 PM


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  • HAL Id : inria-00327774, version 1


Miguel Nicolau, Marc Schoenauer. Evolving Specific Network Statistical Properties using a Gene Regulatory Network Model. European Conference on Complex Systems, Sep 2008, Jerusalem, Israel. ⟨inria-00327774⟩



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