Bridging the Gap Between Evolvable Hardware and Industry Using Cartesian Genetic Programming

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@InCollection{Vasicek:2017:miller,
  author =       "Zdenek Vasicek",
  title =        "Bridging the Gap Between Evolvable Hardware and
                 Industry Using Cartesian Genetic Programming",
  booktitle =    "Inspired by Nature: Essays Presented to Julian F.
                 Miller on the Occasion of his 60th Birthday",
  publisher =    "Springer",
  year =         "2017",
  editor =       "Susan Stepney and Andrew Adamatzky",
  volume =       "28",
  series =       "Emergence, Complexity and Computation",
  chapter =      "2",
  pages =        "39--55",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, EHW",
  isbn13 =       "978-3-319-67996-9",
  DOI =          "doi:10.1007/978-3-319-67997-6_2",
  abstract =     "Advancements in technology developed in the early
                 nineties have enabled researchers to successfully apply
                 techniques of evolutionary computation in various
                 problem domains. As a consequence, a new research
                 direction referred to as evolvable hardware (EHW)
                 focusing on the use of evolutionary algorithms to
                 create specialized electronics has emerged. One of the
                 goals of the early pioneers of EHW was to evolve
                 complex circuits and overcome the limits of traditional
                 design. Unfortunately, evolvable hardware found itself
                 in a critical stage around 2010 and a very pessimistic
                 future for EHW-based digital circuit synthesis was
                 predicted. The problems solved by the community were of
                 the size and complexity of that achievable in fifteens
                 years ago and seldom compete with traditional designs.
                 The scalability problem has been identified as one of
                 the most difficult problems that researchers are faced
                 with and it was not clear whether there existed a path
                 forward that would allow the field to progress. Despite
                 that, researchers have continued to investigate how to
                 overcome the scalability issues and significant
                 progress has been made in the area of evolutionary
                 synthesis of digital circuits in recent years. The goal
                 of this chapter is to summarize the progress in the
                 evolutionary synthesis of gate-level digital circuits,
                 and to identify the challenges that need to be
                 addressed to enable evolutionary methods to penetrate
                 into industrial practice.",
  notes =        "part of \cite{miller60book}
                 https://link.springer.com/bookseries/10624",
}

Genetic Programming entries for Zdenek Vasicek

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