Dear Colleagues,
The paper on complete neural network induction using Darwinian evolution is
now available online both in pdf format and html at:
http://www.gene-expression-programming.com/webpapers/abstracts.asp#14
Ferreira, C., Designing Neural Networks Using Gene Expression Programming.
In A. Abraham, B. de Baets, M. Köppen, and B. Nickolay, eds., Applied Soft
Computing Technologies: The Challenge of Complexity, pages 517-536,
Springer-Verlag, 2006.
ABSTRACT: An artificial neural network with all its elements is a rather
complex structure, not easily constructed and/or trained to perform a
particular task. Consequently, several researchers used genetic algorithms
to evolve partial aspects of neural networks, such as the weights, the
thresholds, and the network architecture. Indeed, over the last decade many
systems have been developed that perform total network induction. In this
work it is shown how the chromosomes of Gene Expression Programming can be
modified so that a complete neural network, including the architecture, the
weights and thresholds, could be totally encoded in a linear chromosome. It
is also shown how this chromosomal organization allows the
training/adaptation of the network using the evolutionary mechanisms of
selection and modification, thus providing an approach to the automatic
design of neural networks. The workings and performance of this new
algorithm are tested on the 6-multiplexer and on the classical exclusive-or
problems.
This paper requires a certain familiarity with the basics of GEP, especially
the head/tail organization, the expression of genes with random constants,
and the type and mechanisms of the genetic operators. For a quick
introduction see my Complex Systems paper:
http://www.gene-expression-programming.com/webpapers/GEP.pdf
For the sample problems of this paper I chose well-known logical functions,
but the beauty of GEP-nets is that they can be used on a multitude of
modeling problems, from nonlinear regression to classification and they are
as good as any GEP system. I guess I’ll have to write a paper on this since
I haven’t seen anyone taking up on this task since I first described this
algorithm in my 2002 book.
Best wishes,
Candida
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Candida Ferreira, Ph.D.
Founder and Director, Gepsoft
http://www.gene-expression-programming.com/author.asp
GEP: Mathematical Modeling by an Artificial Intelligence.
2nd Edition, Springer, 2006
http://www.gene-expression-programming.com/Books/index.asp
GeneXproTools 4.0 -- Data Mining Software
http://www.gepsoft.com/
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