- author = "W. B. Langdon and R. Poli",
- title = "Fitness Causes Bloat: Mutation",
- booktitle = "Proceedings of the First European Workshop on Genetic Programming",
- year = "1998",
- editor = "Wolfgang Banzhaf and Riccardo Poli and Marc Schoenauer and Terence C. Fogarty",
- volume = "1391",
- series = "LNCS",
- pages = "37--48",
- address = "Paris",
- publisher_address = "Berlin",
- month = "14-15 " # apr,
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-540-64360-5",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL.euro98_bloatm.pdf",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL.euro98_bloatm.ps.gz",
-
DOI = "
doi:10.1007/BFb0055926",
- size = "12 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 = "EuroGP'98 Based on \cite{Langdon:1997:bloatMUT}",
- affiliation = "University of Birmingham School of Computer Science B15 2TT Birmingham UK B15 2TT Birmingham UK",
