@TechReport{Langdon97,
  author      = "W. B. Langdon and R. Poli",
  title       = {Fitness Causes Bloat},
  institution = {University of Birmingham, School of Computer Science},
  number      = {CSRP-97-09},
  month       = {February},
  year        = {1997},
  file        = {/1997/CSRP-97-09.ps.gz},
  url         = {ftp://ftp.cs.bham.ac.uk/pub/tech-reports/1997/CSRP-97-09.ps.gz},
  abstract    = {The problem of evolving an artificial ant to follow the
                 Santa Fe trail is used to demonstrate the well known
                 genetic programming feature of growth in solution length.
                 Known variously as ``bloat'', ``redundancy'', ``introns'',
                 ``fluff'', ``Structural Complexity'' with antonyms
                 ``parsimony'', ``Minimum Description Length'' (MDL) and
                 ``Occam's razor''. Comparison with runs with and without
                 fitness selection pressure 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. Since 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 of the same solution. Thus
                 with an unbiased random search we expect longer
                 representations to occur more often and so representation
                 length tends to increase. I.e. fitness based selection
                 leads to bloat.
                 },
		  
notes =           {Updated version in WSC2. 
		  WBL.bloat_wsc2.ps.gz also available in html version},
		  }