Genetic Programming with Local Hill-Climbing   [GP]

by

Iba, H., Garis, H., D., Garis, H., . and Sato, T.

Literature search on Evolutionary ComputationBBase ©1999-2013, Rasmus K. Ursem
     Home · Search · Adv. search · Authors · Login · Add entries   Webmaster
Note to authors: Please submit your bibliography and contact information - online papers are more frequently cited.

Info: Parallel Problem Solving from Nature III (Conference proceedings), 1994, p. 334-343
Keywords:genetic algorithms, genetic programming
Abstract:
"We demonstrate the superior effectiveness of GP+local Hill Climbing [HC] with experiments in Boolean concept formation and symbolic regression". Boolean GP combines GP with Adaptive Logic Network trees. Combination can evove to cope with time varying fitness functions. Numerical GP [FF] combines GP with GMDH (Group Method of Data Handling, Ivakhnenko)
Notes:
PPSN3 see also technical note Iba:1994:GPlHC

LNCS E-print:
Volume   first page   
NB: Papers are in PDF, not all are online, and you need access to Springer's Link archive.
Internet search:Search Google
Search Google Scholar
Search Citeseer using Google
Search Google for PDF
Search Google Scholar for PDF
Search Citeseer for PDF using Google

Review item:

Mark as doublet (will be reviewed)

Print entry




BibTex:
@InProceedings{iba:1994:GPlHCppsn3,
  author =       "Hitoshi Iba and Hugo {de Garis} and Taisuke Sato",
  title =        "Genetic Programming with Local Hill-Climbing",
  booktitle =    "Parallel Problem Solving from Nature III",
  year =         "1994",
  editor =       "Yuval Davidor and Hans-Paul Schwefel and Reinhard
                 M{\"a}nner",
  pages =        "334--343",
  address =      "Jerusalem",
  publisher_address = "Berlin, Germany",
  month =        "9-14 " # oct,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "{"}We demonstrate the superior effectiveness of
                 GP+local Hill Climbing with experiments in Boolean
                 concept formation and symbolic regression{"}. Boolean
                 GP combines GP with Adaptive Logic Network trees.
                 Combination can evove to cope with time varying fitness
                 functions. Numerical GP combines GP with GMDH (Group
                 Method of Data Handling, Ivakhnenko)",
  notes =        "PPSN3 see also technical note Iba:1994:GPlHC",
}