Cartesian Genetic Programming on the GPU

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

@InCollection{Harding:2013:ecgpu,

• author = "Simon Harding and Julian F. Miller",
• title = "Cartesian Genetic Programming on the {GPU}",
• booktitle = "Massively Parallel Evolutionary Computation on {GPGPUs}",
• publisher = "Springer",
• year = "2013",
• editor = "Shigeyoshi Tsutsui and Pierre Collet",
• series = "Natural Computing Series",
• chapter = "12",
• pages = "249--266",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, GPU",
• isbn13 = "978-3-642-37958-1",
• URL = "https://144c912f-b777-4dc5-89cc-51238af78a13.filesusr.com/ugd/5ef763_135e2e412fdd45d7b8aed573b6a277e1.pdf",
• URL = "http://www.springer.com/computer/ai/book/978-3-642-37958-1",
• DOI = "doi:10.1007/978-3-642-37959-8_12",
• abstract = "Cartesian Genetic Programming is a form of Genetic Programming based on evolving graph structures. It has a fixed genotype length and a genotype phenotype mapping that introduces neutrality into the representation. It has been used for many applications and was one of the first Genetic Programming techniques to be implemented on the GPU. In this chapter, we describe the representation in detail and discuss various GPU implementations of it. Later in the chapter, we discuss a recent implementation based on the GPU.net framework.",

}

Genetic Programming entries for Simon Harding Julian F Miller

Citations