University of Hertfordshire

By the same authors

Standard

Evolution of developmental ontogeny for robustly reproducible phenotypes. / Rust, A.G.; Adams, R.G.; George, S.; Bolouri, H.

University of Hertfordshire, 1998. (UH Computer Science Technical Report; Vol. 317).

Research output: Book/ReportOther report

Harvard

Rust, AG, Adams, RG, George, S & Bolouri, H 1998, Evolution of developmental ontogeny for robustly reproducible phenotypes. UH Computer Science Technical Report, vol. 317, University of Hertfordshire.

APA

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.

Vancouver

Rust AG, Adams RG, George S, Bolouri H. Evolution of developmental ontogeny for robustly reproducible phenotypes. University of Hertfordshire, 1998. (UH Computer Science Technical Report).

Author

Rust, A.G. ; Adams, R.G. ; George, S. ; Bolouri, H. / Evolution of developmental ontogeny for robustly reproducible phenotypes. University of Hertfordshire, 1998. (UH Computer Science Technical Report).

Bibtex

@book{58438df4ced94dccbba73289a6a58152,
title = "Evolution of developmental ontogeny for robustly reproducible phenotypes",
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.",
author = "A.G. Rust and R.G. Adams and S. George and H. Bolouri",
year = "1998",
language = "English",
series = "UH Computer Science Technical Report",
publisher = "University of Hertfordshire",

}

RIS

TY - BOOK

T1 - Evolution of developmental ontogeny for robustly reproducible phenotypes

AU - Rust, A.G.

AU - Adams, R.G.

AU - George, S.

AU - Bolouri, H.

PY - 1998

Y1 - 1998

N2 - 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.

AB - 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.

M3 - Other report

T3 - UH Computer Science Technical Report

BT - Evolution of developmental ontogeny for robustly reproducible phenotypes

PB - University of Hertfordshire

ER -