Diversity Control in GP with ADF for Regression Tasks

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  title =        "Diversity Control in GP with ADF for Regression
  author =       "Huayang Xie",
  year =         "2005",
  pages =        "253--1257",
  booktitle =    "AI 2005: Advances in Artificial Intelligence, 18th
                 Australian Joint Conference on Artificial Intelligence,
  editor =       "Shichao Zhang and Ray Jarvis",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3809",
  address =      "Sydney, Australia",
  month =        dec # " 5-9",
  keywords =     "genetic algorithms, genetic programming, diversity
  ISBN =         "3-540-30462-2",
  DOI =          "doi:10.1007/11589990_181",
  size =         "5 pages",
  abstract =     "two-phase diversity control approach to prevent the
                 common problem of the loss of diversity in Genetic
                 Programming with Automatically Defined Functions. While
                 most recent work focuses on diagnosing and remedying
                 the loss of diversity, this approach aims to prevent
                 the loss of diversity in the early stage through a
                 refined diversity control method and a fully covered
                 tournament selection method. The results on regression
                 tasks suggest that these methods can effectively
                 improve the system performance by reducing the
                 incidences of premature convergence and the number of
                 generations needed an optimal solution.",
  notes =        "PART IV: Short Papers",

Genetic Programming entries for Huayang Jason Xie