Nicolau, MiguelMiguelNicolauSchoenauer, MarcMarcSchoenauer2017-01-132017-01-132008 IEEE2008-06-06http://hdl.handle.net/10197/8261IEEE Congress on Evolutionary Computation (CEC 2008) Hong-Kong, China, 1-6 June 2008A novel approach to generating scale-free network topologies is introduced, based on an existing artificial Gene Regulatory Network model. From this model, different interaction networks can be extracted, based on an activation threshold. 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.en© 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Scale-free topologiesComplex networksEvolutionary computationConference Publication3747375410.1109/cec.2008.46313052016-11-15https://creativecommons.org/licenses/by-nc-nd/3.0/ie/