- author = "Wendy Ashlock",
- title = "Using Very Small Population Sizes in Genetic Programming",
- booktitle = "2006 IEEE World Congress on Computational Intelligence, 2006 IEEE Congress on Evolutionary Computation",
- year = "2006",
- pages = "1023--1030",
- address = "Vancouver",
- month = "16-21 " # jul,
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/CEC.2006.1688325",
- size = "8 pages",
-
abstract = "This paper examines the use of very small (4-7)
population sizes in genetic programming. When using
exploitive operators, this results in hillclimbing;
when using exploratory operators this results in
genetic drift. The end result is a different way of
searching the space which gives insight into the
fitness landscape and the nature of the variation
operators used.
This study compares the use of very small population sizes with the use of population sizes up to 1000 for three genetic programming problems: 4-parity using parse trees, Tartarus using ISAc lists, and several versions of plus-onerecall- store (PORS) using parse trees. For 4-parity and Tartarus with 60 ISAc nodes, algorithms with very small population sizes found more solutions faster. For PORS, the effect was less pronounced: more solutions were found, but the algorithm was faster only than when using slightly larger populations. For Tartarus with 30 ISAc nodes, no effect was detected.",
-
notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
the IEE.
IEEE Catalog Number: 06TH8846D IEEE Xplore gives pages = 319--326,",
