Schemas and Genetic Programming

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

@InCollection{oai:CiteSeerPSU:397549,
  title =        "Schemas and Genetic Programming",
  author =       "Andreas Birk and Wolfgang J. Paul",
  booktitle =    "Prerational Intelligence: Adaptive Behavior and
                 Intelligent Systems Without Symbols and Logic {II}",
  publisher =    "Kluwer",
  year =         "2001",
  editor =       "Holk Cruse and Jeffrey Dean and Helge Ritter",
  volume =       "26",
  series =       "Studies in Cognitive Systems",
  pages =        "345--357",
  ebook_pages =  "804--816",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7923-6666-2",
  isbn13 =       "978-94-010-3792-1",
  URL =          "http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-135-22-33673255-0,00.html",
  URL =          "http://www.faculty.iu-bremen.de/birk/publications/schemas_genetic_programming.pdf",
  URL =          "http://arti.vub.ac.be/~cyrano/PUBLICATIONS/schema_gp00.ps.gz",
  URL =          "http://citeseer.ist.psu.edu/397549.html",
  DOI =          "doi:10.1007/978-94-010-0870-9_50",
  citeseer-isreferencedby = "oai:CiteSeerPSU:106696;
                 oai:CiteSeerPSU:67434; oai:CiteSeerPSU:532836;
                 oai:CiteSeerPSU:86635; oai:CiteSeerPSU:54193;
                 oai:CiteSeerPSU:315750; oai:CiteSeerPSU:89833;
                 oai:CiteSeerPSU:66393; oai:CiteSeerPSU:226046;
                 oai:CiteSeerPSU:360779; oai:CiteSeerPSU:193774",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:397549",
  rights =       "unrestricted",
  size =         "13 pages",
  abstract =     "To investigate the mechanisms which enable systems to
                 learn is among the most challenging of research
                 activities. In computer science alone it is pursued by
                 at least three communities (Carbonel 1990; Natarajan
                 1991; Ritter et al. 1991). The overwhelming majority of
                 all studies treats situations with strong inductive
                 bias, i.e. there is a fairly narrow class H of
                 algorithms and the concept or algorithm to be learned
                 is known a priori to lie in that class H.

                 With the help of schemas and genetic programming we
                 describe systems which:

                 interact with the real world

                 make theories about the consequences of their actions
                 and

                 dynamically adjust inductive bias. We present
                 experimental data related to learning geometric
                 concepts and moving a block in a microworld.",
}

Genetic Programming entries for Andreas Birk Wolfgang J Paul

Citations