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        Molecular self-organisation in a developmental model for the evolution of large-scale artificial neural networks

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        903612.pdf (PDF, 193Kb)
        Author
        Bolouri, H.
        Adams, R.G.
        George, S.
        Rust, A.G.
        Attention
        2299/3983
        Abstract
        We argue that molecular self-organisation during embryonic development allows evolution to perform highly nonlinear combinatorial optimisation. A structured approach to architectural optimisation of large-scale Artificial Neural Networks using this principle is presented. We also present simulation results demonstrating the evolution of an edge detecting retina using the proposed methodology.
        Publication date
        1998
        Published in
        Proceedings of the 1998 International Conference on Neural Information Processing and Intelligent Information Systems (ICONIP'98)
        Other links
        http://hdl.handle.net/2299/3983
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