- author = "Tobias Blickle and Lothar Thiele",
- title = "Genetic Programming and Redundancy",
- booktitle = "Genetic Algorithms within the Framework of Evolutionary Computation (Workshop at KI-94, Saarbr{\"u}cken)",
- editor = "J. Hopf",
- publisher = "Max-Planck-Institut f{\"u}r Informatik (MPI-I-94-241)",
-
address = "
Im Stadtwald, Building 44, D-66123 Saarbr{\"u}cken, Germany
",
- pages = "33--38",
- year = "1994",
- keywords = "genetic algorithms, genetic programming",
-
URL = "
http://www.tik.ee.ethz.ch/~tec/publications/bt94/GPandRedundancy.ps.gz",
- size = "6 pages",
- abstract = "The Genetic Programming optimization method (GP) elaborated by John Koza [Koza, 1992] is a variant of Genetic Algorithms. The search space of the problem domain consists of computer programs represented as parse trees, and the crossover operator is realized by an exchange of subtrees. Empirical analyses show that large parts of those trees are never used or evaluated which means that these parts of the trees are irrelevant for the solution or redundant. This paper is concerned with the identification of the redundancy occurring in GP. It starts with a mathematical description of the behaviour of GP and the conclusions drawn from that description among others explain the size problem which denotes the phenomenon that the average size of trees in the population grows with time.",
-
notes = "From GP list Wed, 22 Mar 95 we did some work on the
convergence problem and the redundancy in the trees in
GP. It turned out that bloating is a property of GP
that arises from the fact that more redundant trees
have a higher probability to survive crossover. As a
result, the redundant part of the trees grow bigger and
bigger because the increased proportion of redundant
cut-sites in the tree again lead to a higher
probability to survive crossover.
Gives a formula for tournament size related to proportion of crossover in a generational GP. Ie recommending T=10 for pc=0.9. This does not apply to steady state GA.
",
