The Evolution of Size in Variable Length Representations

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

@InProceedings{langdon:1997:pgSAHCP,

• author = "W. B. Langdon",
• title = "The Evolution of Size in Variable Length Representations",
• booktitle = "1998 IEEE International Conference on Evolutionary Computation",
• year = "1998",
• pages = "633--638",
• address = "Anchorage, Alaska, USA",
• month = "5-9 " # may,
• organisation = "IEEE",
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, structural complexity, introns, Price's Theorem, Santa Fe trail problem, artificial ant, bloat, code growth, competition, fluff, increasing structural complexity, length bias, length-neutral mutation, nonpopulation-based search techniques, population-based search technique, program length increase, program reproduction accuracy, search operators, simulated annealing, size evolution, static evaluation functions, strict hill climbing, subtree-based mutation operator, tree sampling, tree size, unbiased mutation, variable-length representations, competitive algorithms, mathematical operators, programming theory, search problems, simulated annealing, trees (mathematics), variable length codes",
• ISBN = "0-7803-4869-9",
• file = "c109.pdf",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL.wcci98_bloat.pdf",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL.wcci98_bloat.ps.gz",
• DOI = "doi:10.1109/ICEC.1998.700102",
• size = "6 pages",
• abstract = "In many cases programs length's increase (known as 'bloat', 'fluff' and increasing 'structural complexity') during artificial evolution. We show bloat is not specific to genetic programming and suggest it is inherent in search techniques with discrete variable length representations using simple static evaluation functions. We investigate the bloating characteristics of three non-population and one population based search techniques using a novel mutation operator.

  An artificial ant following the Santa Fe trail problem is solved by simulated annealing, hill climbing, strict hill climbing and population based search using two variants of the the new subtree based mutation operator. As predicted bloat is observed when using unbiased mutation and is absent in simulated annealing and both hill climbers when using the length neutral mutation however bloat occurs with both mutations when using a population.

  We conclude that there are two causes of bloat 1) search operators with no length bias tend to sample bigger trees and 2) competition within populations favours longer programs as they can usually reproduce more accurately.",

• notes = "ICEC-98 Held In Conjunction With WCCI-98 --- 1998 IEEE World Congress on Computational Intelligence

  based on \cite{langdon:1997:bloatSAHCP}",

}

Genetic Programming entries for William B Langdon

Citations