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