Evolutionary Developmental Evaluation : the Interplay between Evolution and Development

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@PhdThesis{Hoang:thesis,
  author =       "Tuan-Hao Hoang",
  title =        "Evolutionary Developmental Evaluation : the Interplay
                 between Evolution and Development",
  school =       "Information Technology \& Electrical Engineering,
                 Australian Defence Force Academy, University of New
                 South Wales",
  year =         "2008",
  address =      "Australia",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 Development Evaluation (EDE), Development Tree
                 Adjoining Grammar Guided Genetic Programming (DTAG3P),
                 Evolutionary computation, Developmental biology,
                 Developmental genetics",
  broken =       "http://trove.nla.gov.au/version/49711933",
  URL =          "http://handle.unsw.edu.au/1959.4/44870",
  URL =          "http://unsworks.unsw.edu.au/fapi/datastream/unsworks:8166/SOURCE01.pdf",
  size =         "338 pages",
  language =     "English",
  abstract =     "This thesis was inspired by the difficulties of
                 artificial evolutionary systems in finding elegant and
                 well structured, regular solutions. That is that the
                 solutions found are usually highly disorganised, poorly
                 structured and exhibit limited re-use, resulting in
                 bloat and other problems. This is also true of previous
                 developmental evolutionary systems, where structural
                 regularity emerges only by chance. We hypothesise that
                 these problems might be ameliorated by incorporating
                 repeated evaluations on increasingly difficult problems
                 in the course of a developmental process. This thesis
                 introduces a new technique for learning complex
                 problems from a family of structured increasingly
                 difficult problems, Evolutionary Developmental
                 Evaluation (EDE). This approach appears to give more
                 structured, scalable and regular solutions to such
                 families of problems than previous methods. In
                 addition, the thesis proposes some bio-inspired
                 components that are required by developmental
                 evolutionary systems to take full advantage of this
                 approach. The key part of this is the developmental
                 process, in combination with a varying fitness function
                 evaluated at multiple stages of development, generates
                 selective pressure toward generalisation. This also
                 means that parsimony in structure is selected for
                 without any direct parsimony pressure. As a result, the
                 system encourages the emergence of modularity and
                 structural regularity in solutions. In this thesis, a
                 new genetic developmental system called Developmental
                 Tree Adjoining Grammar Guided Genetic Programming
                 (DTAG3P), is implemented, embodying the requirements
                 above. It is tested on a range of benchmark problems.
                 The results indicate that the method generates more
                 regularly-structured solutions than the competing
                 methods. As a result, the system is able to scale, at
                 least on the problem classes tested, to very complex
                 instances the system encourages the emergence of
                 modularity and structural regularity in solutions. In
                 this thesis, a new genetic developmental system called
                 Developmental Tree Adjoining Grammar Guided Genetic
                 Programming (DTAG3P), is implemented, embodying the
                 requirements above. It is tested on a range of
                 benchmark problems. The results indicate that the
                 method generates more regularly-structured solutions
                 than competing methods. As a result, the system is able
                 to scale, at least on the problem classes tested, to
                 very complex problem instances.",
  notes =        "oai:unsworks.unsw.edu.au:unsworks:8166 Supervisor:
                 Daryl Essam",
}

Genetic Programming entries for Tuan-Hao Hoang

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