Similarity-based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Stephan M. Winkler and Michael Affenzeller and 
                 Bogdan Burlacu and Gabriel Kronberger and Michael Kommenda and 
                 Philipp Fleck",
  title =        "Similarity-based Analysis of Population Dynamics in
                 Genetic Programming Performing Symbolic Regression",
  booktitle =    "Genetic Programming Theory and Practice XIV",
  year =         "2016",
  editor =       "Rick Riolo and Bill Worzel and Brian Goldman and 
                 Bill Tozier",
  address =      "Ann Arbor, USA",
  month =        "19-21 " # may,
  publisher =    "Springer",
  note =         "Forthcoming",
  keywords =     "genetic algorithms, genetic programming, Symbolic
                 Regression, Genetic Programming, Population Dynamics,
                 Genetic and Phenotypic Diversity, Offspring Selection,
  isbn13 =       "978-3-319-97087-5",
  URL =          "",
  abstract =     "Population diversity plays an important role in
                 genetic programming (GP) evolutionary dynamics. In this
                 paper, we use structural and semantic similarity
                 measures to investigate the evolution of diversity in
                 three GP algorithmic flavours: standard GP, offspring
                 selection GP (OS-GP), and age-layered population
                 structure GP (ALPS-GP). Empirical measurements on two
                 symbolic regression benchmark problems reveal important
                 differences between the dynamics of the tested
                 configurations. In standard GP, after an initial
                 decrease, population diversity remains almost constant
                 until the end of the run. The higher variance of the
                 phenotypic similarity values suggests that small
                 changes on individual genotypes have significant
                 effects on their corresponding phenotypes. By contrast,
                 strict offspring selection within the OS-GP algorithm
                 causes a significantly more pronounced diversity loss
                 at both genotypic and, in particular, phenotypic
                 levels. The pressure for adaptive change increases
                 phenotypic robustness in the face of genotypic
                 perturbations, leading to less genotypic variability on
                 the one hand, and very low phenotypic diversity on the
                 other hand. Finally, the evolution of similarities in
                 ALPS-GP follows a periodic pattern marked by the time
                 interval when the bottom layer is reinitialized with
                 new individuals. This pattern is easily noticed in the
                 lower layers characterized by shorter migration
                 intervals, and becomes less and less noticeable on the
                 upper layers.",
  notes =        "

                 Part of \cite{Tozier:2016:GPTP} to be published after
                 the workshop",

Genetic Programming entries for Stephan M Winkler Michael Affenzeller Bogdan Burlacu Gabriel Kronberger Michael Kommenda Philipp Fleck