@TechReport{Langdon97,
  author      = "B. Langdon and R. Poli",
  title       = {Causes Bloat: Mutation},
  institution = {University of Birmingham, School of Computer Science},
  number      = {CSRP-97-16},
  month       = {May},
  year        = {1997},
  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.
                 },
}