Genetic Programming of an Artificial Neural Network for Robust Control of a 2-D Path Following Robot

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

@InProceedings{Roy:2008:IDETC/CIE,

• author = "Anthony M. Roy and Erik K. Antonsson and Andrew A. Shapiro",
• title = "Genetic Programming of an Artificial Neural Network for Robust Control of a 2-D Path Following Robot",
• booktitle = "28th Computers and Information in Engineering Conference IDETC/CIE2008",
• year = "2008",
• volume = "1",
• pages = "799--805",
• address = "Brooklyn, New York, USA",
• month = aug # " 3-6",
• publisher = "ASME",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-0-7918-4325-3",
• DOI = "doi:10.1115/DETC2008-50137",
• abstract = "Genetic Programs that have phenotypes created by the application of genotypes comprising rules are robust and highly scalable. Such encodings are useful for complex applications such as controller design. This paper outlines an evolutionary algorithm capable of creating a controller for 2 DOF, path following robot. The controllers are embodied by Artificial Neural Networks capable of full functionality despite multiple failures.",

}

Genetic Programming entries for Anthony M Roy Erik K Antonsson Andrew A Shapiro

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