On the Theory of Designing Circuits using Genetic Programming and a Minimum of Domain Knowledge   [GP]

by

Andre, D., Bennett III, F., H., Koza, J., R. and Keane, M., A.

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Info: Proceedings of the 1998 IEEE World Congress on Computational Intelligence (Conference proceedings), 1998, p. 130-135
Keywords:genetic algorithms, genetic programming
Abstract:
The problem of analog circuit design [CD] is a difficult problem that is generally viewed as requiring human intelligence to solve. Considerable progress has been made in automating the design of certain categories of purely digital circuits; [DC] however, the design of analog electrical circuits and mixed analog-digital circuits has not proved to be as amenable to automation. When critical analog circuits are required for a project, skilled and highly trained experts are necessary. Previous work on applying genetic programming to [GP] the design of analog circuits has proved to be successful at evolving a wide variety of circuits, including filters, amplifiers, and computational circuits; [CC] however, previous approaches have required the specification of an appropriate embryonic circuit. This paper explores a method to eliminate even this small amount of problem specific knowledge, and, in addition, proves that the representation used is capable of producing all circuits.
Notes:
ICEC-98 Held In Conjunction With WCCI-98 --- 1998 IEEE World Congress on Computational Intelligence
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BibTex:
@InProceedings{andre:1998:tdcGPmdk,
  author =       "David Andre and Forrest H {Bennett III} and John Koza
                 and Martin A. Keane",
  title =        "On the Theory of Designing Circuits using Genetic
                 Programming and a Minimum of Domain Knowledge",
  booktitle =    "Proceedings of the 1998 IEEE World Congress on
                 Computational Intelligence",
  year =         "1998",
  pages =        "130--135",
  address =      "Anchorage, Alaska, USA",
  month =        "5-9 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  file =         "c023.pdf",
  size =         "6 pages",
  abstract =     "The problem of analog circuit design is a difficult
                 problem that is generally viewed as requiring human
                 intelligence to solve. Considerable progress has been
                 made in automating the design of certain categories of
                 purely digital circuits; however, the design of analog
                 electrical circuits and mixed analog-digital circuits
                 has not proved to be as amenable to automation. When
                 critical analog circuits are required for a project,
                 skilled and highly trained experts are necessary.
                 Previous work on applying genetic programming to the
                 design of analog circuits has proved to be successful
                 at evolving a wide variety of circuits, including
                 filters, amplifiers, and computational circuits;
                 however, previous approaches have required the
                 specification of an appropriate embryonic circuit. This
                 paper explores a method to eliminate even this small
                 amount of problem specific knowledge, and, in addition,
                 proves that the representation used is capable of
                 producing all circuits.",
  notes =        "ICEC-98 Held In Conjunction With WCCI-98 --- 1998 IEEE
                 World Congress on Computational Intelligence",
}