Discovery of Neural Network Learning Rules Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@TechReport{radi:CSRP-97-21,

• author = "Amr M. Radi and Riccardo Poli",
• title = "Discovery of Neural Network Learning Rules Using Genetic Programming",
• institution = "University of Birmingham, School of Computer Science",
• number = "CSRP-97-21",
• month = sep,
• year = "1997",
• file = "/1997/CSRP-97-21.ps.gz",
• URL = "ftp://ftp.cs.bham.ac.uk/pub/tech-reports/1997/CSRP-97-21.ps.gz",
• reportfilename = "pub/tech-reports/1997/CSRP-97-21.ps.gz",
• keywords = "genetic algorithms, genetic programming",
• abstract = "The development of the backpropagation learning rule has been a land mark in neural networks. It provides a computational method for training multi layer networks. Unfortunately, backpropagation suffers from several problems. a new technique based upon Genetic Programming (GP) is proposed to overcome some of these problems. We have used GP to discover new supervised learning algorithms. A set of such learning algorithms has been compared with the Standard BackPropagation (SBP) learning algorithm on different problems and has been shown to provide better performances. This study indicates that there exist many supervised learning algorithms better than, but similar to, SBP and that GP can be used to discover them.",

}

Genetic Programming entries for Amr Mohamed Mahmoud Khairat Radi Riccardo Poli

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