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        Evolution of developmental ontogeny for robustly reproducible phenotypes

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        CSTR 317.pdf (PDF, 1Mb)
        Author
        Rust, A.G.
        Adams, R.G.
        George, S.
        Bolouri, H.
        Attention
        2299/5373
        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.
        Publication date
        1998
        Other links
        http://hdl.handle.net/2299/5373
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