Evolutionary Module Acquisition

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{angeline:1993:ema,
  author =       "Peter J. Angeline and Jordan Pollack",
  title =        "Evolutionary Module Acquisition",
  booktitle =    "Proceedings of the Second Annual Conference on
                 Evolutionary Programming",
  year =         "1993",
  editor =       "D. Fogel and W. Atmar",
  pages =        "154--163",
  address =      "La Jolla, CA, USA",
  month =        "25-26 " # feb,
  organisation = "The Evolutionary Programming Society",
  keywords =     "genetic algorithms, genetic programming, FSM, GLiB",
  URL =          "http://www.demo.cs.brandeis.edu/papers/ep93.pdf",
  URL =          "http://www.demo.cs.brandeis.edu/papers/ep93.ps.gz",
  URL =          "http://www.natural-selection.com/Library/1993/ep93.ps.Z",
  size =         "9 pages",
  abstract =     "Evolutionary programming and genetic algorithms share
                 many features, not the least of which is a reliance of
                 an analogy to natural selection over a population as a
                 means of implementing search. With their commonalities
                 come shared problems whose solutions can be
                 investigated at a higher level and applied to both. One
                 such problem is the manipulation of solution parameters
                 whose values encode a desirable sub-solution. In this
                 paper, we define a superset of evolutionary programming
                 and genetic algorithms, called evolutionary algorithms,
                 and demonstrate a method of automatic modularization
                 that protects promising partial solutions and speeds
                 acquisition time.",
  notes =        "Artificial Ant (John Muir). Finite State Machines.
                 Genetic Library Builder

                 ",
}

Genetic Programming entries for Peter John Angeline Jordan B Pollack