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dc.contributor.authorRust, A.G.
dc.contributor.authorAdams, R.G.
dc.contributor.authorGeorge, S.
dc.contributor.authorBolouri, H.
dc.date.accessioned2011-01-04T15:24:39Z
dc.date.available2011-01-04T15:24:39Z
dc.date.issued1996
dc.identifier.citationRust , A G , Adams , R G , George , S & Bolouri , H 1996 , Artificial evolution: modelling the development of the retina . UH Computer Science technical Report , vol. 255 , University of Hertfordshire .
dc.identifier.otherPURE: 100167
dc.identifier.otherPURE UUID: 31242680-721b-4754-bb94-e6afbd943473
dc.identifier.otherdspace: 2299/5096
dc.identifier.urihttp://hdl.handle.net/2299/5096
dc.description.abstractThe evolution of neural systems relies on the repeated modification of developmental programmes contained within genes. This paper proposes that to efficiently investigate artificial evolution, developmental processes must first be characterised and encoded. The development processes themselves are inherently simple, representing a form of emergent self-organisation. A model of artificial neural structure self-organisation is presented, where development occurs across different levels of scale and development processes are divided into phases. Within this framework, a Developmental Artificial Neural Network (DANN) has been implemented to model the growth of neuron-neuron connections in both 2D and 3D. The development of a biologically inspired, artifcial retina is being investigated. This is believed to be the first reported 3D DANN.en
dc.language.isoeng
dc.publisherUniversity of Hertfordshire
dc.relation.ispartofseriesUH Computer Science technical Report
dc.titleArtificial evolution: modelling the development of the retinaen
dc.contributor.institutionCentre for Computer Science and Informatics Research
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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