Investigations into Lamarckism, Baldwinism and Local Search in Grammatical Evolution Guided by Reinforcement

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

@Article{journals/cai/MingoAMA13,
  author =       "Jack Mario Mingo and Ricardo Aler and 
                 Dario Maravall and Javier {de Lope Asiain}",
  title =        "Investigations into Lamarckism, Baldwinism and Local
                 Search in Grammatical Evolution Guided by
                 Reinforcement",
  journal =      "Computing and Informatics",
  year =         "2013",
  number =       "3",
  volume =       "32",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  bibdate =      "2013-08-16",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/cai/cai32.html#MingoAMA13",
  pages =        "595--627",
  URL =          "http://www.cai.sk/ojs/index.php/cai/article/view/1735",
  size =         "33 pages",
  abstract =     "Grammatical Evolution Guided by Reinforcement is an
                 extension of Grammatical Evolution that tries to
                 improve the evolutionary process adding break a
                 learning process for all the individuals in the
                 population. With this aim, each individual is given a
                 chance to learn through a reinforcement learning
                 mechanism during its lifetime. The learning process is
                 completed with a Lamarckian mechanism in which an
                 original genotype is replaced by the best learnt
                 genotype for the individual. In a way, Grammatical
                 Evolution Guided by Reinforcement shares an important
                 feature with other hybrid algorithms, i.e. global
                 search in the evolutionary process combined with local
                 search in the learning process. In this paper the role
                 of the Lamarck Hypothesis is reviewed and a solution
                 inspired only in the Baldwin effect is included as
                 well. Besides, different techniques about the trade-off
                 between exploitation and exploration in the
                 reinforcement learning step followed by Grammatical
                 Evolution Guided by Reinforcement are studied. In order
                 to evaluate the results, the system is applied on two
                 different domains: a simple autonomous navigation
                 problem in a simulated Kephera robot and a typical
                 Boolean function problem.",
}

Genetic Programming entries for Jack Mario Mingo Ricardo Aler Mur Dario Maravall Gomez-Allende Javier de Lope

Citations