Grammars for Learning Control Knowledge with GP

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

@InProceedings{aler:2001:glckg,
  author =       "Ricardo Aler and Daniel Borrajo and Pedro Isasi",
  title =        "Grammars for Learning Control Knowledge with GP",
  booktitle =    "Proceedings of the 2001 Congress on Evolutionary
                 Computation CEC2001",
  year =         "2001",
  pages =        "1220--1227",
  address =      "COEX, World Trade Center, 159 Samseong-dong,
                 Gangnam-gu, Seoul, Korea",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "27-30 " # may,
  organisation = "IEEE Neural Network Council (NNC), Evolutionary
                 Programming Society (EPS), Institution of Electrical
                 Engineers (IEE)",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, computational
                 linguistics, grammars, learning (artificial
                 intelligence), search problems, AI planning system,
                 EVOCK, Evolution of Control Knowledge, GP based system,
                 PRODIGY, ad-hoc mechanisms, blocksworld domain, control
                 knowledge learning, control rule language, control rule
                 syntax, control rules, grammar approach flexibility,
                 grammar specific, grammars, language restrictions,
                 search space, standard GP, standard select type",
  ISBN =         "0-7803-6658-1",
  URL =          "http://scalab.uc3m.es/~dborrajo/papers/cec01.ps.gz",
  DOI =          "doi:10.1109/CEC.2001.934330",
  size =         "8 pages",
  abstract =     "In standard GP there are no constraints on the
                 structure to evolve: any combination of functions and
                 terminals is valid. However, sometimes GP is used to
                 evolve structures that must respect some constraints.
                 Instead of ad-hoc mechanisms, grammars can be used to
                 guarantee that individuals comply with the language
                 restrictions. In addition, grammars permit great
                 flexibility to define the search space. EVOCK
                 (Evolution of Control Knowledge) is a GP based system
                 that learns control rules for PRODIGY, an AI planning
                 system. EVOCK uses a grammar to constrain individuals
                 to PRODIGY 4.0 control rule syntax. The authors
                 describe the grammar specific details of EVOCK. Also,
                 the grammar approach flexibility has been used to
                 extend the control rule language used by EVOCK in
                 earlier work. Using this flexibility, tests were
                 performed to determine whether using combinations of
                 several types of control rules for planning was better
                 than using only the standard select type. Experiments
                 have been carried out in the blocksworld domain that
                 show that using the combination of types of control
                 rules does not get better individuals, but it produces
                 good individuals more frequently",
  notes =        "CEC-2001 - A joint meeting of the IEEE, Evolutionary
                 Programming Society, Galesia, and the IEE.

                 IEEE Catalog Number = 01TH8546C,

                 Library of Congress Number = .

                 EVOCK, PRODIGY 4.0, blocksworld",
}

Genetic Programming entries for Ricardo Aler Mur Daniel Borrajo Pedro Isasi Vinuela

Citations