Developmental Evaluation in Genetic Programming: the Preliminary Results

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{eurogpMcKayHoangEssamNguyen:,
  author =       "Robert Ian McKay and Tuan Hao Hoang and 
                 Daryl Leslie Essam and Xuan Hoai Nguyen",
  title =        "Developmental Evaluation in Genetic Programming: the
                 Preliminary Results",
  editor =       "Pierre Collet and Marco Tomassini and Marc Ebner and 
                 Steven Gustafson and Anik\'o Ek\'art",
  booktitle =    "Proceedings of the 9th European Conference on Genetic
                 Programming",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "3905",
  year =         "2006",
  address =      "Budapest, Hungary",
  month =        "10 - 12 " # apr,
  organisation = "EvoNet",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-33143-3",
  pages =        "280--289",
  DOI =          "doi:10.1007/11729976_25",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  abstract =     "This paper investigates developmental evaluation in
                 Genetic Programming (GP). Extant GP systems, including
                 developmental GP systems, typically exhibit modular and
                 hierarchical structure only to the degree it is
                 built-in by the designer; by contrast, biological
                 systems exhibit a high degree of organisation in their
                 genotypes. We hypothesise that even when GP systems are
                 subject to changing environments, for which the
                 adaptability arising from modular structure would be
                 advantageous, the benefit is at the species rather than
                 individual level, so that selection is very weak. By
                 contrast, biological systems are selected repeatedly
                 throughout their development process. We suggest that
                 this difference is crucial; that if an individual is
                 evaluated multiple times throughout its development,
                 then modular structure can provide an adaptive
                 advantage to that individual, and hence can be selected
                 for by evolution. We investigate this hypothesis using
                 Tree Adjoining Grammar Guided Genetic Programming
                 (TAG3P), which has good properties for supporting
                 evaluation during incremental development. Our
                 preliminary results show that developmental TAG3P
                 outperforms both original TAG3P and standard tree-based
                 GP on an appropriate problem, in ways which suggest
                 that modular solutions may have been developed.",
  notes =        "Part of \cite{collet:2006:GP} EuroGP'2006 held in
                 conjunction with EvoCOP2006 and EvoWorkshops2006",
}

Genetic Programming entries for R I (Bob) McKay Tuan-Hao Hoang Daryl Essam Nguyen Xuan Hoai

Citations