Evolution of developmental ontogeny for robustly reproducible phenotypes

A.G. Rust, R.G. Adams, S. George, H. Bolouri

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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.
Original languageEnglish
PublisherUniversity of Hertfordshire
Publication statusPublished - 1998

Publication series

NameUH Computer Science Technical Report
PublisherUniversity of Hertfordshire
Volume317

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