GP-Lab: The Genetic Programming Laboratory

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@MastersThesis{Glaholt:mastersthesis,
  author =       "William Edward Glaholt",
  title =        "GP-Lab: The Genetic Programming Laboratory",
  school =       "Computer Science, California State University,
                 Sacramento",
  year =         "2004",
  type =         "Masters of Science",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.theglaholts.net/gplab/GPLab-ThesisDoc%20Final.pdf",
  size =         "136 pages",
  abstract =     "Evolutionary Programming, also known as Genetic
                 Programming ({"}GP{"}), is an Artificial Intelligence
                 paradigm in which an algorithm is synthesised in the
                 style of Charles Darwin's theory of Evolution.
                 Algorithms are generated through 'reverse-engineering,'
                 the concept in which a desired solution is known, as
                 are the tools, functions, and objects used to generate
                 the solution, but the algorithm that solves the
                 solution is unknown. GP creates a random population of
                 'individuals', evaluates those individuals for fitness
                 (a term used to judge how 'close' the solution is to a
                 targeted solution), then iteratively creates new
                 generations by 'cross-breeding' genes of the more fit
                 individuals, evaluating, crossbreeding, and so on until
                 the 'best' solution is found. Current tools in the
                 discipline are generally targeted towards solving one
                 explicit problem, or require actual source code
                 modification of the software packages1 in order to
                 effect such a generation. In addition, the solutions
                 generated by existing software tools are not normally
                 immediately usable, are obscure, or are in 'LISP-style'
                 function format, which may be difficult to translate to
                 the average programmer. GP-Lab is based upon, and is an
                 extension of the tool created in a previous Master's
                 thesis by Michael Kramer ({"}GAPS - Genetic Algorithm
                 Programming System{"}, 1996) [1], as well as several
                 other current tools, e.g. 'lil-gp' and 'GARAGE'. GP-Lab
                 adds many user-flexible features, including graphic
                 outputs, direct-to-C compile-ready code solution
                 translation, and a full, extensible procedural
                 programming language with user-created functions. As
                 such, GP-Lab is a tool targeted toward the average
                 programmer who has a known desired solution, a set of
                 tools upon which the solution may be based, and wishes
                 to know the algorithm used to solve that solution.",
  notes =        "Approved by: Dr. Du Zhang, Advisor and Committee Chair
                 W. Scott Gordon, Associate Professor",
}

Genetic Programming entries for William Glaholt

Citations