Fitness Causes Bloat: Mutation

Created by W.Langdon from gp-bibliography.bib Revision:1.8656

@InProceedings{Langdon:1997:bloatMUTet,

• author = "W. B. Langdon and R. Poli",
• title = "Fitness Causes Bloat: Mutation",
• booktitle = "ET'97 Theory and Application of Evolutionary Computation",
• year = "1997",
• editor = "Chris Clack and Kanta Vekaria and Nadav Zin",
• pages = "59--77",
• address = "University College London, UK",
• month = "15 " # dec,
• keywords = "genetic algorithms, genetic programming",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/bloat_springer.ET97.camera_ready.ps.gz",
• URL = "http://www.cs.ucl.ac.uk/isrg//et97/papers.htm#wbl",
• size = "10 pages",
• abstract = "The problem of evolving, using mutation, an artificial ant to follow the Santa Fe trail is used to study the well known genetic programming feature of growth in solution length. Known variously as bloat, fluff and increasing structural complexity, this is often described in terms of increasing redundancy in the code caused by introns. Comparison between runs with and without fitness selection pressure, backed by Price's Theorem, shows the tendency for solutions to grow in size is caused by fitness based selection. We argue that such growth is inherent in using a fixed evaluation function with a discrete but variable length representation. With simple static evaluation search converges to mainly finding trial solutions with the same fitness as existing trial solutions. In general variable length allows many more long representations of a given solution than short ones. Thus in search (without a length bias) we expect longer representations to occur more often and so representation length to tend to increase. I.e. fitness based selection leads to bloat.",
• notes = "http://www.cs.ucl.ac.uk/isrg/et97/ As \cite{Langdon:1997:bloatMUT} but with improved experiments",

}

Genetic Programming entries for William B Langdon Riccardo Poli

Citations