Genetic Programming and Emergent Intelligence

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

@InCollection{kinnear:angeline,
  title =        "Genetic Programming and Emergent Intelligence",
  author =       "Peter John Angeline",
  booktitle =    "Advances in Genetic Programming",
  publisher =    "MIT Press",
  editor =       "Kenneth E. {Kinnear, Jr.}",
  year =         "1994",
  pages =        "75--98",
  chapter =      "4",
  size =         "23 pages",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://citeseer.ist.psu.edu/187189.html",
  URL =          "http://citeseer.ist.psu.edu/cache/papers/cs/1870/http:zSzzSzwww.natural-selection.comzSzpeoplezSzpjazSzdocszSzaigp.pdf/angeline94genetic.pdf",
  URL =          "http://cognet.mit.edu/sites/default/files/books/9780262277181/pdfs/9780262277181_chap4.pdf",
  URL =          "http://www.amazon.co.uk/Advances-Genetic-Programming-Complex-Adaptive/dp/0262111888",
  abstract =     "Genetic programming is but one of several problem
                 solving methods based on a computational analogy to
                 natural evolution. Such algorithms, collectively titled
                 evolutionary computations, embody dynamics that permit
                 task specific knowledge to emerge while solving the
                 problem. In contrast to the traditional knowledge
                 representations of artificial intelligence, this method
                 of problem solving is termed emergent intelligence.
                 This chapter describes some of the basics of emergent
                 intelligence, its implementation in evolutionary
                 computations, and its contributions to genetic
                 programming. Demonstrations and guidelines on how to
                 exploit emergent intelligence to extend the problem
                 solving capabilities of genetic programming and other
                 evolutionary computations are also presented.",
  notes =        "'Contrasts GP with other Weak/strong AI methods,
                 credit assignment, USEFUL, diplodity=redundancy=good,
                 hierarchical code/decode of subroutines better than
                 Koza ADF Loads of references'

                 I realized that inherent dynamics of genetic
                 programming encouraged certain emergent properties. The
                 most important of these is that introns emerge
                 naturally from the process to protect the developing
                 program from crossover. Others in the field think this
                 extra stuff in the genetic program is a bad thing,
                 reflected by their choice of the term 'bloating' for
                 the effect. This chapter is the first to take a
                 positive view on GP introns and other emergent
                 phenomena. I think this is the first paper to associate
                 the 'extra' code in genetic programs with the intron
                 concept.",
}

Genetic Programming entries for Peter John Angeline

Citations