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Genetic Generation of Both the Weights and Architecture for a Neural Network

, and . International Joint Conference on Neural Networks, IJCNN-91, II, page 397--404. Washington State Convention and Trade Center, Seattle, WA, USA, IEEE Computer Society Press, (8-12 July 1991)

Abstract

This paper shows how to find both the weights and architecture for a neural network (including the number of layers, the number of processing elements per layer, and the connectivity between processing elements). This is accomplished using a recently developed extension to the genetic algorithm which genetically breeds a population of LISP symbolic expressions (S-expressions) of varying size and shape until the desired performance by the network is successfully evolved. The new genetic programming paradigm is applied to the problem of generating a neural network for the one-bit adder.

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