A coarse-coding framework for a gene-regulatory-based artificial neural tissue

Authors:
Jekanthan Thangavelautham;Gabriele M. T. D’Eleuterio
Affiliations:
Institute for Aerospace Studies, University of Toronto, Toronto, Ontario, Canada;Institute for Aerospace Studies, University of Toronto, Toronto, Ontario, Canada
Venue:
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Year:
2005

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Abstract

A developmental Artificial Neural Tissue (ANT) architecture inspired by the mammalian visual cortex is presented. It is shown that with the effective use of gene regulation that large phenotypes in the form of Artificial Neural Tissues do not necessarily pose an impediment to evolution. ANT includes a Gene Regulatory Network that controls cell growth/death and activation/inhibition of the tissue based on a coarse-coding framework. This scalable architecture can facilitate emergent (self-organized) task decomposition and require limited task specific information compared with fixed topologies. Only a global fitness function (without biasing a particular task decomposition strategy) is specified and self-organized task decomposition is achieved through a process of gene regulation, competitive coevolution, cooperation and specialization.