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Artificial Regulatory Networks and the Evolution of Neural Networks
'''Artificial Regulatory Networks and the Evolution of Neural Networks'''


In this project we will study the design and evolution of Artificial Regulatory Networks (ARN) applied to the evolution of Artificial Neural Networks (ANN). ARNs are based on a genome representation generated by a duplication/divergence process. The network can be evolved to match output functions. The goal is to adapt the ARN and evolve ANNs when performing a certain task.
In this project we will study the design and evolution of Artificial Regulatory Networks (ARN) applied to the evolution of Artificial Neural Networks (ANN). ARNs are based on a genome representation generated by a duplication/divergence process. The network can be evolved to match output functions. The goal is to adapt the ARN and evolve ANNs when performing a certain task.


Participants: Jorge Tavares, Anna Fedor, Cornelia Kreutzer
 
''Interested participants'': [[Jorge Tavares]], [[Anna Fedor]], [[Cornelia Kreutzer]]
 
Back to [[Group Pages]]

Revision as of 13:40, 17 June 2006

Artificial Regulatory Networks and the Evolution of Neural Networks

In this project we will study the design and evolution of Artificial Regulatory Networks (ARN) applied to the evolution of Artificial Neural Networks (ANN). ARNs are based on a genome representation generated by a duplication/divergence process. The network can be evolved to match output functions. The goal is to adapt the ARN and evolve ANNs when performing a certain task.


Interested participants: Jorge Tavares, Anna Fedor, Cornelia Kreutzer

Back to Group Pages