Probabilistic Model Building GP with Belief Propagation

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  title =        "Probabilistic Model Building {GP} with Belief
  author =       "Hiroyuki Sato and Yoshihiko Hasegawa and 
                 Danushka Bollegala and Hitoshi Iba",
  pages =        "2089--2096",
  booktitle =    "Proceedings of the 2012 IEEE Congress on Evolutionary
  year =         "2012",
  editor =       "Xiaodong Li",
  month =        "10-15 " # jun,
  DOI =          "doi:10.1109/CEC.2012.6256483",
  address =      "Brisbane, Australia",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Estimation of
                 distribution algorithms",
  abstract =     "Estimation of distribution algorithms (EDAs) which
                 deal with tree structures as GP are called as
                 probabilistic model building GPs (PMBGPs), and they
                 show better search performance than GP in many
                 problems. A problem of prototype tree-based method, a
                 type of PMBGPs, is that samplings do not always
                 generate the most probable solution, which is the
                 individual with the highest probability and reflects a
                 learnt distribution most. This problem wastes a part of
                 learning and increases the number of evaluations to get
                 an optimum solution. In order to overcome this
                 difficulty, this paper proposes a hybrid approach using
                 Belief propagation (BP) in sampling process. BP is an
                 inference algorithm on graphical models and can
                 generate the most probable solution. By applying our
                 approach to benchmark tests, we show that the proposed
                 method is more effective than PLS alone.",
  notes =        "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
                 EPS and the IET.",

Genetic Programming entries for Hiroyuki Sato Yoshihiko Hasegawa Danushka Bollegala Hitoshi Iba