The Relationship between Semantic Distance and Performance in Dynamic Symbolic Regression Problems

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

@InProceedings{tuite:mendel:2014,
  author =       "Cliodhna Tuite and Michael O'Neill and 
                 Anthony Brabazon",
  title =        "The Relationship between Semantic Distance and
                 Performance in Dynamic Symbolic Regression Problems",
  booktitle =    "Mendel 2014 The 20th International Conference on Soft
                 Computing",
  year =         "2014",
  address =      "Brno, Czech Republic",
  keywords =     "genetic algorithms, genetic programming, dynamic
                 environments, symbolic regression, semantic distance",
  URL =          "http://ncra.ucd.ie/papers/mendel2014_tuite.pdf",
  abstract =     "Several methods which apply genetic programming (GP)
                 in dynamic optimisation environments implicitly assume
                 that the smaller the semantic change in the
                 optimization goal, the better the adaptation of the GP
                 population to the new target. However, GP searches over
                 genetic operator-based fitness landscapes. As such,
                 relative distances between solution points in genetic
                 operator-based landscapes may not be related to the
                 semantic distances between points. Our experiments
                 examine whether decreasing the semantic distance
                 between first and second-period target functions in
                 symbolic regression problems result in improved
                 performance in the second period. As a control, we also
                 investigate how re-initialising the GP population in
                 the second period performs in comparison with using a
                 continuous GP population across the two periods. We
                 find that decreasing the semantic distance does result
                 in better performance in the second period, and that
                 re-initializing the GP population under performs a
                 continuous population at low semantic distances.",
  notes =        "http://www.mendel-conference.org/tmp/ScheduleMendel2014e.pdf",
}

Genetic Programming entries for Cliodhna Tuite Michael O'Neill Anthony Brabazon

Citations