- author = "Kenneth E. {Kinnear, Jr.}",
- title = "Generality and Difficulty in Genetic Programming: Evolving a Sort",
- year = "1993",
- booktitle = "Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-93",
- editor = "Stephanie Forrest",
- publisher = "Morgan Kaufmann",
- pages = "287--294",
- month = "17-21 " # jul,
- address = "University of Illinois at Urbana-Champaign",
- keywords = "genetic algorithms, genetic programming",
- size = "8 pages",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/ftp.io.com/papers/kinnear.icga93.ps.Z",
- abstract = "application of GP to evolving sorting algorithms and the lessons learned from this. Plus the discovery of a connection between size and generality.",
-
notes = "Adding inverse prog size decreases size of progs and
makes them more general.
Ref \cite{Bickel:1989:tsrGA} Tree structured rules in GAs Kinnear IEEE Press, ICNN U M O'Reilly and F. Oppacher 'An experimental Perspective on Genetic Programming' in 'Parallel Problem solving from nature' R.Manner and B. Manderick (eds) Holland:Elsevier.
Loads of references on Steady State v generational (also see kim's own reference)
Various fiddling to find balance of size parameters. Various terminal/function sets tried (less powerful -> more difficult) Smaller successful programs more general.
David R. White says reproduced without problem May 2009",
