Long-Term Stability of Genetic Programming Landscapes

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

@InProceedings{langdon:2017:LHS,

• author = "William B. Langdon",
• title = "Long-Term Stability of Genetic Programming Landscapes",
• booktitle = "GECCO 2017 Workshop on Landscape-Aware Heuristic Search",
• year = "2017",
• editor = "Nadarajen Veerapen and Fabio Daolio and Arnaud Liefooghe and Sebastien Verel and Gabriela Ochoa",
• address = "Berlin",
• note = "No paper, presentation only",
• keywords = "genetic algorithms, genetic programming, Genetic programming, Convergence, unbounded evolution",
• size = "8 pages",
• abstract = "Evolving binary mux-6 trees for up to 100000 generations, during which some programs grow to more than a hundred million nodes, suggests the landscape which GP explores contains some very smooth regions. Although the GP population evolves under crossover, our unbounded GP appears not to evolve building blocks. We do see periods of tens even hundreds of generations where even although each member of the population occupies a different point in the genotypic search space, they are lie at exactly the same point in the phenotypic landscape. Phenotypic convergence whilst retaining genotypic diversity is typical of GP and, we suggest inherent in highly redundant variable length representations.

  Based on technical report \href{http://www.cs.ucl.ac.uk/fileadmin/UCL-CS/research/Research_Notes/RN_17_05.pdf} {RN/17/05} \cite{Langdon:2017:GECCO}",

}

Genetic Programming entries for William B Langdon

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