A Flexible Representation for Genetic Programming from Natural Language Processing

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@PhdThesis{hoai_thesis,
  author =       "Nguyen Xuan Hoai",
  title =        "A Flexible Representation for Genetic Programming from
                 Natural Language Processing",
  school =       "Australian Defence force Academy, University of New
                 South Wales",
  year =         "2004",
  address =      "Australia",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming,
                 grammar-guided, genotype space, natural language
                 processing, phenotype space, tree adjoining grammars
                 (TAGs)",
  URL =          "http://www.library.unsw.edu.au/~thesis/adt-ADFA/uploads/approved/adt-ADFA20051024.152230/public/01front.pdf",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/hoai_thesis.tar.gz",
  URL =          "http://handle.unsw.edu.au/1959.4/38750",
  size =         "262 pages",
  abstract =     "This thesis principally addresses some problems in
                 genetic programming (GP) and grammar-guided genetic
                 programming (GGGP) arising from the lack of operators
                 able to make small and bounded changes on both genotype
                 and phenotype space. It proposes a new and flexible
                 representation for genetic programming, using a
                 state-of-the-art formalism from natural language
                 processing, Tree Adjoining Grammars (TAGs). It
                 demonstrates that the new TAG-based representation
                 possesses two important properties: non-fixed arity and
                 locality. The former facilitates the design of new
                 operators, including some which are bio-inspired, and
                 others able to make small and bounded changes. The
                 latter ensures that bounded changes in genotype space
                 are reflected in bounded changes in phenotype
                 space.

                 With these two properties, the thesis shows how some
                 well-known difficulties in standard GP and GGGP
                 tree-based representations can be solved in the new
                 representation. These difficulties have been previously
                 attributed to the treebased nature of the
                 representations; since TAG representation is also
                 tree-based, it has enabled a more precise delineation
                 of the causes of the difficulties.

                 Building on the new representation, a new grammar
                 guided GP system known as TAG3P has been developed, and
                 shown to be competitive with other GP and GGGP
                 systems.

                 A new schema theorem, explaining the behaviour of TAG3P
                 on syntactically constrained domains, is
                 derived.

                 Finally, the thesis proposes a new method for
                 understanding performance differences between GP
                 representations requiring different ways to bound the
                 search space, eliminating the effects of the bounds
                 through multi-objective approaches.",
  notes =        "separate files",
}

Genetic Programming entries for Nguyen Xuan Hoai

Citations