Evolution of circuits in hardware and the evolvability of artificial development

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  author =       "Tuze Kuyucu",
  title =        "Evolution of circuits in hardware and the evolvability
                 of artificial development",
  school =       "Department of Electronics, University of York",
  year =         "2010",
  address =      "UK",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming, Evolvable hardware, EHW,
                 artificial development, evolutionary computation,
                 bio-inspired computing, gene regulatory network,
                 multicellular organisation",
  URL =          "http://etheses.whiterose.ac.uk/1020/1/FinalSubmission_Thesis.pdf",
  URL =          "http://etheses.whiterose.ac.uk/1020/",
  size =         "250 pages",
  abstract =     "Automatic design of digital electronic circuits via
                 evolutionary algorithms is a promising area of
                 research. When evolved intrinsically on real hardware,
                 evolved circuits are guaranteed to work and the
                 emergence of novel and unconventional circuits is
                 likely. However, evolution of digital circuits on real
                 hardware can cause various reliability issues. Thus,
                 key mechanisms that produce reliable evolution of
                 digital circuits on a hardware platform are developed
                 and explained in the first part of this thesis.

                 On the other hand, the evolution of complex and
                 scalable designs without any assistance is thwarted due
                 to increasingly large genomes. Using traditional
                 circuit design knowledge to assist evolutionary
                 algorithms, the evolution of scalable circuits becomes
                 feasible, but the results found in such experiments are
                 neither novel anymore nor are they competitive with
                 engineered designs.

                 A novel, biologically inspired gene regulatory network
                 based multicellular artificial developmental model is
                 introduced in this thesis. This developmental model is
                 evolved to build digital circuits that can
                 automatically scale to larger designs. However, the
                 results achieved still remain inferior to engineered
                 digital circuit designs.

                 Evolving a developmental system for the design of
                 engineering systems or computational paradigms provides
                 a variety of desirable properties, such as fault
                 tolerance, adaptivity, and scalable designs automation.
                 However, developmental systems in their role as
                 computational networks are as yet poorly understood.
                 Many mechanisms and parameters that a developmental
                 system comprises are based on various assumptions,
                 their biological counterparts, or educated guesses.
                 There is a lack of understanding of the roles of these
                 mechanisms and parameters in forming an evolvable
                 platform for evolutionary computation.

                 Initially, various experiments are shown to demonstrate
                 the evolvability of the new developmental system. A
                 thorough investigation is then undertaken in order to
                 obtain large amounts of empirical data that yields a
                 better understanding of some of the crucial
                 developmental mechanisms and parameters on the
                 evolvability of multicellular developmental systems.",
  notes =        "Available under License Creative Commons
                 Attribution-Noncommercial-Share Alike 2.0 UK: England &
                 Wales. 6Mb Item Type: Thesis (PhD) ID Code: 1020
                 Deposited By: Mr. Tuze Kuyucu Deposited On: 16 Feb 2011
                 12:40 Last Modified: 16 Feb 2011 12:40",

Genetic Programming entries for Tuze Kuyucu