Grammar Design for Derivation Tree Based Genetic Programming Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Stefan Forstenlechner and Miguel Nicolau and 
                 David Fagan and Michael O'Neill",
  title =        "Grammar Design for Derivation Tree Based Genetic
                 Programming Systems",
  booktitle =    "EuroGP 2016: Proceedings of the 19th European
                 Conference on Genetic Programming",
  year =         "2016",
  month =        "30 " # mar # "--1 " # apr,
  editor =       "Malcolm I. Heywood and James McDermott and 
                 Mauro Castelli and Ernesto Costa and Kevin Sim",
  series =       "LNCS",
  volume =       "9594",
  publisher =    "Springer Verlag",
  address =      "Porto, Portugal",
  pages =        "199--214",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-30668-1",
  DOI =          "doi:10.1007/978-3-319-30668-1_13",
  abstract =     "Grammar-based genetic programming systems have gained
                 interest in recent decades and are widely used
                 nowadays. Although researchers normally present the
                 grammar used to solve a certain problem, they seldom
                 write about processes used to construct the grammar.
                 This paper sheds some light on how to design a grammar
                 that not only covers the search space, but also
                 supports the search process in finding good solutions.
                 The focus lies on context free grammar guided systems
                 using derivation tree crossover and mutation, in
                 contrast to linearised grammar based systems. Several
                 grammars are presented encompassing the search space of
                 sorting networks and show concepts which apply to
                 general grammar design. An analysis of the search
                 operators on different grammar is undertaken and
                 performance examined on the sorting network problem.
                 The results show that the overall structure for
                 derivation trees created by the grammar has little
                 effect on the performance, but still affects the
                 genetic material changed by search operators.",
  notes =        "Part of \cite{Heywood:2016:GP} EuroGP'2016 held in
                 conjunction with EvoCOP2016, EvoMusArt2016 and

Genetic Programming entries for Stefan Forstenlechner Miguel Nicolau David Fagan Michael O'Neill