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{{CSSS 2006--Santa Fe}}
{{CSSS 2006--Santa Fe}}
'''Artificial Regulatory Networks and the Evolution of Neural Networks'''
'''Neuro-Cellular Automata'''


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.
A new type of Cellular Automata is presented and studied. On this automata, the standard way of representing the rules is replaced by an Artificial Neural Network, thus having a more biological inspired automata. It is described the motivation for the development for this kind of automata, as well as, the study that shows its development. The study uses the simple 1D Cellular Automata, enabling an understanding of the needed complexity for the Neural Networks, how to evaluate the automata by using complexity measures, as well as the evolution, of simple Neuro-Cellular Automata, as means for the design of such systems.





Revision as of 18:03, 9 August 2006

CSSS 2006 Santa Fe

Neuro-Cellular Automata

A new type of Cellular Automata is presented and studied. On this automata, the standard way of representing the rules is replaced by an Artificial Neural Network, thus having a more biological inspired automata. It is described the motivation for the development for this kind of automata, as well as, the study that shows its development. The study uses the simple 1D Cellular Automata, enabling an understanding of the needed complexity for the Neural Networks, how to evaluate the automata by using complexity measures, as well as the evolution, of simple Neuro-Cellular Automata, as means for the design of such systems.


Interested participants: Jorge Tavares, Anna Fedor, Cornelia Kreutzer

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