Towards Industrial Strength Automated Design of Analog Electrical Circuits by Means of Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "John R. Koza and Lee W. Jones and Martin A. Keane and 
                 Matthew J. Streeter",
  title =        "Towards Industrial Strength Automated Design of Analog
                 Electrical Circuits by Means of Genetic Programming",
  booktitle =    "Genetic Programming Theory and Practice {II}",
  year =         "2004",
  editor =       "Una-May O'Reilly and Tina Yu and Rick L. Riolo and 
                 Bill Worzel",
  chapter =      "8",
  pages =        "121--142",
  address =      "Ann Arbor",
  month =        "13-15 " # may,
  publisher =    "Springer",
  note =         "pages missing?",
  keywords =     "genetic algorithms, genetic programming, Automated
                 design, automated circuit synthesis, analog circuits,
                 amplifier, evolvable hardware, developmental process",
  ISBN =         "0-387-23253-2",
  URL =          "",
  DOI =          "doi:10.1007/0-387-23254-0_8",
  size =         "22 pages",
  abstract =     "It has been previously established that genetic
                 programming can be used as an automated invention
                 machine to synthesise designs for complex structures.
                 In particular, genetic programming has automatically
                 synthesized structures that infringe, improve upon, or
                 duplicate the functionality of 21 previously patented
                 inventions (including six 21st-century patented analog
                 electrical circuits) and has also generated two
                 patentable new inventions (controllers). There are
                 seven promising factors suggesting that these previous
                 results can be extended to deliver industrial-strength
                 automated design of analog circuits, but two
                 countervailing factors. This chapter explores the
                 question of whether the seven promising factors can
                 overcome the two countervailing factors by reviewing
                 progress on an ongoing project in which we are
                 employing genetic programming to synthesise an
                 amplifier circuit. The work involves a multiobjective
                 fitness measure consisting of 16 different elements
                 measured by five different test fixtures. The chapter
                 describes five ways of using general domain knowledge
                 applicable to all analog circuits, two ways for
                 employing problem-specific knowledge, four ways of
                 improving on previously published genetic programming
                 techniques, and four ways of grappling with the
                 multiobjective fitness measures associated with
                 real-world design problems.",
  notes =        "part of \cite{oreilly:2004:GPTP2}",

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