@inproceedings (langdon:1997:pgSAHCP,
  author =	{W. B. Langdon},
  title =	{The Evolution of Size in Variable Length Representations},
  booktitle =	{1998 IEEE International Conference on Evolutionary Computation},
  year =	1998,
  editor = 	{},
  volume =	{},
  series =	{},
  pages = 	{},
  address = 	{Anchorage, Alaska, USA},
  publisher_address = 	{},
  month = 	{5-9 May},
  organisation ={IEEE},
  publisher = 	{},
  note =	{},
  keywords =    {genetic algorithms, genetic programming, structural complexity, introns, Price's Theorem},
  ISBN =        {},
  url =         {ftp://ftp.cs.bham.ac.uk/pub/authors/W.B.Langdon/papers/WBL.wcci98_bloat.ps.gz},
  size = 	{6 pages},
  abstract =	{
In many cases programs length's increase (known as "bloat", "fluff"
and increasing "structural complexity") during artificial evolution.
We show bloat is not specific to genetic programming and suggest it is
inherent in search techniques with discrete variable length
representations using simple static evaluation functions.  We
investigate the bloating characteristics of three non-population and
one population based search techniques using a novel mutation
operator.

An artificial ant following the Santa Fe trail problem is solved by
simulated annealing, hill climbing, strict hill climbing and
population based search using two variants of the the new subtree
based mutation operator.  As predicted bloat is observed when using
unbiased mutation and is absent in simulated annealing and both hill
climbers when using the length neutral mutation however bloat occurs
with both mutations when using a population.

We conclude that there are two causes of bloat 1) search operators
with no length bias tend to sample bigger trees and 2) competition
within populations favours longer programs as they can usually
reproduce more accurately.
},
  notes =	{ICEC'98 Held In Conjunction With WCCI'98 --- 1998
IEEE World Congress on Computational Intelligence

based on langdon:1997:bloatSAHCP
}
)