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.
- Design Engineering Division and Computers in Engineering Division
Genetic Programming of an Artificial Neural Network for Robust Control of a 2-D Path Following Robot
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Roy, AM, Antonsson, EK, & Shapiro, AA. "Genetic Programming of an Artificial Neural Network for Robust Control of a 2-D Path Following Robot." Proceedings of the ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 1: 34th Design Automation Conference, Parts A and B. Brooklyn, New York, USA. August 3–6, 2008. pp. 799-805. ASME. https://doi.org/10.1115/DETC2008-50137
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