A schema theory analysis of mutation size biases in genetic programming with linear representations

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@TechReport{McPhee00-24,
  author =       "Nicholas Freitag McPhee and Riccardo Poli and 
                 Jon E Rowe",
  title =        "A schema theory analysis of mutation size biases in
                 genetic programming with linear representations",
  institution =  "University of Birmingham, School of Computer Science",
  number =       "CSRP-00-24",
  month =        nov,
  year =         "2000",
  email =        "N.F.McPhee@cs.bham.ac.uk, R.Poli@cs.bham.ac.uk
                 N.F.McPhee@cs.bham.ac.uk",
  keywords =     "genetic algorithms, genetic programming",
  file =         "/2000/CSRP-00-24.ps.gz",
  URL =          "ftp://ftp.cs.bham.ac.uk/pub/tech-reports/2000/CSRP-00-24.ps.gz",
  abstract =     "In recent work we showed how developments in GP schema
                 theory can be used to better understand the biases
                 induced by the standard subtree crossover when genetic
                 programming is applied to variable length linear
                 structures. In this paper we use the schema theory to
                 better understand the biases induced on linear
                 structures by two common GP subtree mutation operators:
                 FULL and GROW mutation. In both cases we find that the
                 operators do have quite specific biases and typically
                 strongly oversample shorter strings.",
}

Genetic Programming entries for Nicholas Freitag McPhee Riccardo Poli Jonathan E Rowe

Citations