Evolutionary Discovery of Learning Rules for Feedforward Neural Networks with Step Activation Function
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{radi:1999:EDLRFNNSAF,
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author = "Amr Radi and Riccardo Poli",
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title = "Evolutionary Discovery of Learning Rules for
Feedforward Neural Networks with Step Activation
Function",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference",
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year = "1999",
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editor = "Wolfgang Banzhaf and Jason Daida and
Agoston E. Eiben and Max H. Garzon and Vasant Honavar and
Mark Jakiela and Robert E. Smith",
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volume = "2",
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pages = "1178--1183",
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address = "Orlando, Florida, USA",
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publisher_address = "San Francisco, CA 94104, USA",
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month = "13-17 " # jul,
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publisher = "Morgan Kaufmann",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-55860-611-4",
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URL = "http://citeseer.ist.psu.edu/329940.html",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco1999/GP-428.attempt2.pdf",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco1999/GP-428.attempt2.ps",
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abstract = "Neural networks with step activation function can be
very efficient ways of performing non linear mappings.
However, no standard learning algorithm exists for
training this kind of neural networks. In this work we
use Genetic Programming (GP) to discover supervised
learning algorithms which can train neural networks
with step activation function. Thanks to GP, a new
learning algorithm has been discovered which has been
shown to provide good performance.",
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notes = "GECCO-99 A joint meeting of the eighth international
conference on genetic algorithms (ICGA-99) and the
fourth annual genetic programming conference (GP-99)",
- }
Genetic Programming entries for
Amr Mohamed Mahmoud Khairat Radi
Riccardo Poli
Citations