Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Models of massive parallelism: analysis of cellular automata and neural networks
Models of massive parallelism: analysis of cellular automata and neural networks
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Takeover time curves in random and small-world structured populations
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)
Takeover times on scale-free topologies
Proceedings of the 9th annual conference on Genetic and evolutionary computation
The influence of scaling and assortativity on takeover times in scale-free topologies
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Effects of scale-free and small-world topologies on binary coded self-adaptive CEA
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Using feedback in a regulatory network computational device
Proceedings of the 13th annual conference on Genetic and evolutionary computation
ReNCoDe: a regulatory network computational device
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
The squares problem and a neutrality analysis with ReNCoDe
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
The Regulatory Network Computational Device
Genetic Programming and Evolvable Machines
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The generation of network topologies with specific, user-specified statistical properties is addressed using an Evolutionary Algorithm that is seeded by an Artificial Gene Regulatory Network Model. The work presented here extends previous work where the proposed approach was demonstrated to be able to evolve scale-free topologies. The present results reinforce the applicability of the proposed method, showing that the evolution of small-world topologies is also possible, but requires a carefully crafted fitness function.