# An Evolutionary Method to Find Good Building-Blocks for Architectures of Artificial Neural Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

@InProceedings{friedrich:1996:emfgbb,
author =       "Christoph M. Friedrich and Claudio Moraga",
title =        "An Evolutionary Method to Find Good Building-Blocks
for Architectures of Artificial Neural Networks",
booktitle =    "Proceedings of the Sixth International Conference on
Information Processing and Management of Uncertainty in
Knowledge-Based Systems (IPMU '96)",
year =         "1996",
pages =        "951--956",
keywords =     "genetic algorithms, genetic programming",
broken =       "ftp://archive.cis.ohio-state.edu/pub/neuroprose/friedrich.ipmu96.ps.Z",
URL =          "http://citeseer.ist.psu.edu/friedrich96evolutionary.html",
abstract =     "This paper deals with the combination of Evolutionary
Algorithms and Artificial Neural Networks (ANN). A new
method is presented, to find good building-blocks for
architectures of Artificial Neural Networks. The method
is based on {\em Cellular Encoding}, a representation
scheme by F. Gruau, and on Genetic Programming by J.
Koza. First it will be shown that a modified Cellular
Encoding technique is able to find good architectures
even for non-boolean networks. With the help of a
graph-database and a new graph-rewriting method, it is
secondly possible to build architectures from modular
structures. The information about building-blocks for
architectures is obtained by statistically analyzing
the data in the graph-database. Simulation results for
two real-world problems are given.",
}



Genetic Programming entries for Christoph M Friedrich Claudio Moraga

Citations