Learning Action Strategies for Planning Domains using Genetic Programming

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

  author =       "John Levine and David Humphreys",
  title =        "Learning Action Strategies for Planning Domains using
                 Genetic Programming",
  booktitle =    "Applications of Evolutionary Computing,
                 EvoWorkshops2003: Evo{BIO}, Evo{COP}, Evo{IASP},
                 Evo{MUSART}, Evo{ROB}, Evo{STIM}",
  year =         "2003",
  editor =       "G{\"u}nther R. Raidl and Stefano Cagnoni and 
                 Juan Jes\'us Romero Cardalda and David W. Corne and 
                 Jens Gottlieb and Agn\`es Guillot and Emma Hart and 
                 Colin G. Johnson and Elena Marchiori and Jean-Arcady Meyer and 
                 Martin Middendorf",
  volume =       "2611",
  series =       "LNCS",
  pages =        "684--695",
  address =      "University of Essex, England, UK",
  publisher_address = "Berlin",
  month =        "14-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 computation, applications",
  isbn13 =       "978-3-540-00976-4",
  URL =          "http://www.cis.strath.ac.uk/~johnl/papers/levine-evostim03.pdf",
  URL =          "http://citeseer.ist.psu.edu/569259.html",
  DOI =          "doi:10.1007/3-540-36605-9_62",
  size =         "13 pages",
  abstract =     "There are many different approaches to solving
                 planning problems, one of which is the use of domain
                 specific control knowledge to help guide a domain
                 independent search algorithm. This paper presents
                 L2Plan which represents this control knowledge as an
                 ordered set of control rules, called a policy, and
                 learns using genetic programming. The genetic program's
                 crossover and mutation operators are augmented by a
                 simple local search. L2Plan was tested on both the
                 blocks world and briefcase domains. In both domains,
                 L2Plan was able to produce policies that solved all the
                 test problems and which outperformed the hand-coded
                 policies written by the authors.",
  notes =        "EvoWorkshops2003",

Genetic Programming entries for John Levine David Humphreys