A dynamic Lattice to Evolve Hierarchically Shared Subroutines: DL'GP

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

@InProceedings{racine:1998:dlehss,
  author =       "Alain Racine and Marc Schoenauer and Philippe Dague",
  title =        "A dynamic Lattice to Evolve Hierarchically Shared
                 Subroutines: DL'GP",
  booktitle =    "Proceedings of the First European Workshop on Genetic
                 Programming",
  year =         "1998",
  editor =       "Wolfgang Banzhaf and Riccardo Poli and 
                 Marc Schoenauer and Terence C. Fogarty",
  volume =       "1391",
  series =       "LNCS",
  pages =        "220--232",
  address =      "Paris",
  publisher_address = "Berlin",
  month =        "14-15 " # apr,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-64360-5",
  DOI =          "doi:10.1007/BFb0055941",
  size =         "13 pages",
  abstract =     "Our purpose is to enhance performance of Genetic
                 Programming (GP) search. For this, we have been develop
                 a homogeneous system allowing to construct
                 simultaneously a solution and sub-parts of it within a
                 GP framework. This problem is a crucial point in GP
                 research lately since this is intimately linked with
                 building blocks existence problem. we present an
                 'on-going' work concerning DL GP Dynamic Lattice
                 Genetic Programming a new GP system to evolve shared
                 specific modules using a hierarchical cooperative
                 coevolution paradigm. This scheme attempts to improve
                 efficiency of GP by taking one's inspiration of
                 organisation of natural entities, especially the
                 emergence of complexity. In particular, DL GP does not
                 require heuristic knowledge. Different credit
                 assignment strategies are presented to compute modules
                 fitness. DL GP approach attempts to reduce the global
                 depth of a tree-solution and avoids multiple searches
                 of the same sub-components. Moreover modules induction
                 improves 'readability' of GP outputs. In particular,
                 local evolutionary process is applied on the different
                 set of subroutines in order to do converged each
                 population toward a specific ability which remains at
                 disposal of higher level subroutines. Problem
                 decomposition and sub-tasks distribution is emergent
                 through the lattice.",
  notes =        "EuroGP'98",
  affiliation =  "C.M.A.P. Ecole Polytechnique 91128 Palaiseau France
                 91128 Palaiseau France",
}

Genetic Programming entries for Alain Racine Marc Schoenauer Philippe Dague

Citations