Evolving Scale-Free Topologies using a Gene Regulatory Network Model
Miguel Nicolau and Marc Schoenauer
In: CEC'08, 1-6 June 2008, Hong-Kong.
A novel approach to generating scale-free network
topologies is introduced, based on an existing artificial
Gene Regulatory Network model, from which the underlying
regulation network is extracted. By using an Evolutionary
Computation approach, the model is allowed to evolve, in
order to reach specific network statistical measures. The results
obtained show that, when the model uses a duplication and
divergence initialisation, such as seen in nature, the resulting
regulation networks not only are closer in topology to scale-free
networks, but also exhibit a much higher potential for evolution.