Genetic Programming on GPGPU cards using EASEA

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

@InCollection{Maitre:2013:ecgpu,

• author = "Ogier Maitre",
• title = "Genetic Programming on {GPGPU cards} using {EASEA}",
• booktitle = "Massively Parallel Evolutionary Computation on {GPGPUs}",
• publisher = "Springer",
• year = "2013",
• editor = "Shigeyoshi Tsutsui and Pierre Collet",
• series = "Natural Computing Series",
• chapter = "11",
• pages = "227--248",
• keywords = "genetic algorithms, genetic programming, GPU",
• isbn13 = "978-3-642-37958-1",
• URL = "http://www.springer.com/computer/ai/book/978-3-642-37958-1",
• DOI = "doi:10.1007/978-3-642-37959-8_11",
• abstract = "Genetic programming is one of the most powerful evolutionary paradigms because it allows us to optimise not only the parameter space but also the structure of a solution. The search space explored by genetic programming is therefore huge and necessitates a very large computing power which is exactly what GPGPUs can provide. This chapter will show how Koza-like tree-based genetic programming can be efficiently ported onto GPGPU processors.",

}

Genetic Programming entries for Ogier Maitre

Citations