Evolutionary Discovery of Learning Rules for Feedforward Neural Networks with Step Activation Function

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{radi:1999:EDLRFNNSAF,

• author = "Amr Radi and Riccardo Poli",
• title = "Evolutionary Discovery of Learning Rules for Feedforward Neural Networks with Step Activation Function",
• booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference",
• year = "1999",
• editor = "Wolfgang Banzhaf and Jason Daida and Agoston E. Eiben and Max H. Garzon and Vasant Honavar and Mark Jakiela and Robert E. Smith",
• volume = "2",
• pages = "1178--1183",
• address = "Orlando, Florida, USA",
• publisher_address = "San Francisco, CA 94104, USA",
• month = "13-17 " # jul,
• publisher = "Morgan Kaufmann",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "1-55860-611-4",
• URL = "http://citeseer.ist.psu.edu/329940.html",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco1999/GP-428.attempt2.pdf",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco1999/GP-428.attempt2.ps",
• 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.",
• 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