Routine Human-Competitive Machine Intelligence by Means of Genetic Programming

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

@InCollection{koza:2003:SPIE,
  author =       "John R. Koza and Matthew J. Streeter and 
                 Martin A. Keane",
  title =        "Routine Human-Competitive Machine Intelligence by
                 Means of Genetic Programming",
  booktitle =    "Applications and Science of Neural Networks, Fuzzy
                 Systems, and Evolutionary Computation VI",
  publisher =    "SPIE",
  year =         "2003",
  editor =       "Bruno Bosacchi and David B. Fogel and 
                 James C. Bezdek",
  volume =       "5200",
  series =       "Proceedings of SPIE",
  pages =        "1--15",
  address =      "San Diego, California",
  note =         "Keynote Address",
  email =        "john@johnkoza.com",
  keywords =     "genetic algorithms, genetic programming, automated
                 inventions, parametrised topology, analog circuit
                 synthesis, controller synthesis",
  URL =          "http://www.genetic-programming.com/jkpdf/spie2003.pdf",
  DOI =          "doi:10.1117/12.512613",
  size =         "15 pages",
  abstract =     "Genetic programming is a systematic method for getting
                 computers to automatically solve a problem. Genetic
                 programming starts from a high-level statement of what
                 needs to be done and automatically creates a computer
                 program to solve the problem. The paper demonstrates
                 that genetic programming (1) now routinely delivers
                 high-return human-competitive machine intelligence; (2)
                 is an automated invention machine; (3) can
                 automatically create a general solution to a problem in
                 the form of a parameterised topology; and (4) has
                 delivered a progression of qualitatively more
                 substantial results in synchrony with five
                 approximately order-of-magnitude increases in the
                 expenditure of computer time. Recent results involving
                 the automatic synthesis of the topology and sizing of
                 analog electrical circuits and controllers demonstrate
                 these points.",
}

Genetic Programming entries for John Koza Matthew J Streeter Martin A Keane

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