dc.contributor.author | Rust, A.G. | |
dc.contributor.author | Adams, R.G. | |
dc.contributor.author | George, S. | |
dc.contributor.author | Bolouri, H. | |
dc.date.accessioned | 2011-02-22T13:30:24Z | |
dc.date.available | 2011-02-22T13:30:24Z | |
dc.date.issued | 1998 | |
dc.identifier.citation | Rust , A G , Adams , R G , George , S & Bolouri , H 1998 , Evolution of developmental ontogeny for robustly reproducible phenotypes . UH Computer Science Technical Report , vol. 317 , University of Hertfordshire . | |
dc.identifier.other | dspace: 2299/5373 | |
dc.identifier.uri | http://hdl.handle.net/2299/5373 | |
dc.description.abstract | Development has been used by a number of researchers as an efficient means of nonlinearly decoding genetic information is evolutionary systems. We show that developmental routines which do not utilise cell-cell interactions result in poor performance under noisy conditions. Addition of interactive rules permits self-organisation during development and produces robust mappings from genotype to phenotype even under noisy conditions. As a case study, we present the evolution of an edge-detecting artificial retina. The model is capable of creating three dimensional, multi-layer neural networks by modelling the development of neuron-to-neuron connectivity. Incorporating interactive overgrowth and pruning is shown to overcome the poor performance of intrinsic-only growth under noisy conditions. Staged evolution (speciation) of these processes is propose and demonstrated as an effective means of evolving such complex developmental programmes. | en |
dc.format.extent | 1906779 | |
dc.language.iso | eng | |
dc.publisher | University of Hertfordshire | |
dc.relation.ispartofseries | UH Computer Science Technical Report | |
dc.title | Evolution of developmental ontogeny for robustly reproducible phenotypes | en |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |