GP-induced and explicit bloating of the seeds in incremental GP improves evolutionary success

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

  author =       "Ivan Tanev and Tuze Kuyucu and Katsunori Shimohara",
  title =        "{GP-induced} and explicit bloating of the seeds in
                 incremental GP improves evolutionary success",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2014",
  volume =       "15",
  number =       "1",
  pages =        "37--60",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Snakebot,
                 Bloat, Genetic transposition, Incremental GP",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-013-9192-y",
  size =         "24 pages",
  abstract =     "The parsimony control in genetic programming (GP) is
                 one of the limiting factors in the quick evolution of
                 efficient solutions. A variety of parsimony pressure
                 methods have been developed to address this issue. The
                 effects of these methods on the efficiency of evolution
                 are recognised to depend on the characteristics of the
                 applied problem domain. On the other hand, the
                 implications of using parsimony pressure in evolving
                 the seeds for incremental genetic programming (IGP) are
                 still poorly known and remain uninvestigated. In this
                 work we present a study on the cumulative effect of the
                 bloat and the seeding of the initial population on the
                 efficiency of incremental evolution of simulated
                 snake-like robot (Snakebot). In the proposed IGP, the
                 task of coevolving the locomotion gaits and sensing of
                 the bot in a challenging environment is decomposed into
                 two sub-tasks, implemented as two consecutive
                 evolutionary stages. First, to evolve the pools of
                 sensor less Snakebots, we use GP featuring the
                 following three bloat-control methods: (1) linear
                 parametric parsimony pressure, (2) lexicographic
                 parsimony pressure and (3) no bloat control. During the
                 second stage of IGP, we use these pools to seed the
                 initial population of Snakebots applying two methods of
                 seeding: canonical seeding and seeding inspired by
                 genetic transposition (GT).",
  notes =        "Transponson, cf McClintock Maize. GT. ODE simulator.
                 Genome 15*3 ??? or 3??? ADF 'Parsimony
                 ...implications ...on fitness' p51. Best with no
                 parsimony on seeds p53. Cone shape used by sidewiding
                 robot to turn. Apex of cone at either head or tail of
                 robot, fig10. IGP. Delphi

Genetic Programming entries for Ivan T Tanev Tuze Kuyucu Katsunori Shimohara