Cartesian genetic programming approach for embryonic fabric architecture

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Malhotra:2016:ICICM,

• author = "Gayatri Malhotra",
• booktitle = "2016 6th International Conference on Information Communication and Management (ICICM)",
• title = "Cartesian genetic programming approach for embryonic fabric architecture",
• year = "2016",
• pages = "285--290",
• abstract = "The Cartesian genetic programming (CGP) considers grid of nodes to represent a genotype. In the corresponding phenotype each node represents a processing element. The processing element has similar structure as of smallest embryonic fabric element. It can be an embryonic molecule where all molecules combine and create an embryonic cell equivalent to a circuit. The evolutionary algorithm applied to genotypes select the fittest. The evaluated genotype determines the configuration data for embryonic cell. The configuration data generation is automated with this approach. As well this can lead to optimised embryonic fabric structure if optimisation by evolutionary algorithm is used. In this paper the CGP approach is applied to generate configuration data for embryonic fabric. The approach is simulated for 1-bit adder circuit.",
• keywords = "genetic algorithms, genetic programming, Cartesian genetic programming",
• DOI = "doi:10.1109/INFOCOMAN.2016.7784259",
• month = oct,
• notes = "Also known as \cite{7784259}",

}

Genetic Programming entries for Gayatri Malhotra

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