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

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

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

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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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.

Original language	English
Title of host publication	Proceedings of the 1998 International Conference on Neural Information Processing and Intelligent Information Systems (ICONIP'98)
Pages	797-800
Volume	2
Publication status	Published - 1998

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

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.",

author = "H. Bolouri and R.G. Adams and S. George and A.G. Rust",

year = "1998",

language = "English",

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Molecular self-organisation in a developmental model for the evolution of large-scale artificial neural networks. / Bolouri, H.; Adams, R.G.; George, S. et al.
Proceedings of the 1998 International Conference on Neural Information Processing and Intelligent Information Systems (ICONIP'98) . Vol. 2 1998. p. 797-800.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Molecular self-organisation in a developmental model for the evolution of large-scale artificial neural networks

AU - Bolouri, H.

AU - Adams, R.G.

AU - George, S.

AU - Rust, A.G.

PY - 1998

Y1 - 1998

N2 - 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.

AB - 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.

M3 - Conference contribution

VL - 2

SP - 797

EP - 800

BT - Proceedings of the 1998 International Conference on Neural Information Processing and Intelligent Information Systems (ICONIP'98)

ER -

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

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