Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
How learning can guide evolution
Adaptive individuals in evolving populations
A classification of long-term evolutionary dynamics
ALIFE Proceedings of the sixth international conference on Artificial life
Neuroanatomy in a computational perspective
The handbook of brain theory and neural networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Evolving the Topology and the Weights of Neural Networks Using a Dual Representation
Applied Intelligence
Evolving modular genetic regulatory networks
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Supplementing evolutionary developmental systems with abstract models of neurogenesis
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Journal of Cognitive Neuroscience
Computational consequences of a bias toward short connections
Journal of Cognitive Neuroscience
Proceedings of the 10th annual conference on Genetic and evolutionary computation
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We study the selective advantage of modularity in artificially evolved networks. Modularity abounds in complex systems in the real world. However, experimental evidence for the selective advantage of network modularity has been elusive unless it has been supported or mandated by the genetic representation. The evolutionary origin of modularity is thus still debated: whether networks are modular because of the process that created them, or the process has evolved to produce modular networks. It is commonly argued that network modularity is beneficial under noisy conditions, but experimental support for this is still very limited. In this article, we evolve nonlinear artificial neural network classifiers for a binary classification task with a modular structure. When noise is added to the edge weights of the networks, modular network topologies evolve, even without representational support.