Created by W.Langdon from gp-bibliography.bib Revision:1.2031
@InProceedings{Langdon:1997:bloatMUT,
author = "W. B. Langdon and R. Poli",
title = "Fitness Causes Bloat: Mutation",
booktitle = "Late Breaking Papers at the GP-97 Conference",
year = "1997",
editor = "John Koza",
pages = "132--140",
address = "Stanford, CA, USA",
publisher_address = "Stanford, California, 94305-3079 USA",
month = "13-16 " # jul,
publisher = "Stanford Bookstore",
keywords = "genetic algorithms, genetic programming",
ISBN = "0-18-206995-8",
file = "/1997/CSRP-97-16.ps.gz",
URL = "
ftp://ftp.cs.bham.ac.uk/pub/tech-reports/1997/CSRP-97-16.ps.gz",
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.",
size = "9 pages",
notes = "GP-97LB Also available as University of Birmingham,
School of Computer Science, CSRP-97-16
The email address for the bookstore for mail orders is
mailorder@bookstore.stanford.edu Phone no 415-329-1217
or 800-533-2670",
}
Genetic Programming entries for William B Langdon Riccardo Poli