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

Jekanthan Thangavelautham, Gabriele M.T. D'Eleuterio

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

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 arid 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.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages67-77
Number of pages11
DOIs
StatePublished - 2005
Externally publishedYes
Event8th European Conference on Advances in Artificial Life, ECAL 2005 - Canterbury, United Kingdom
Duration: Sep 5 2005Sep 9 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3630 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th European Conference on Advances in Artificial Life, ECAL 2005
Country/TerritoryUnited Kingdom
CityCanterbury
Period9/5/059/9/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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