A Parallel Approach to Grammatical Evolution in Python

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "Michael Stallard",
  title =        "A Parallel Approach to Grammatical Evolution in
  year =         "2006",
  keywords =     "genetic algorithms, genetic programming, Grammatical
  URL =          "http://www.cs.bath.ac.uk/~mdv/courses/CM30082/projects.bho/2005-6/stallard-mj-dissertation-2005-6.pdf",
  size =         "158 pages",
  abstract =     "Grammatical Evolution is the creation of computer
                 programs using Evolutionary Computation over the search
                 space of a language grammar. Previous systems have been
                 written in C, C++ or Java, however due to the compiled
                 nature of the languages used in the implementations
                 there is the disadvantage of a clear separation between
                 the Grammatical Evolution system and the generated
                 solutions. Furthermore, these systems lack clarity and
                 readability in their code and design. An implementation
                 of Grammatical Evolution in the Python programming
                 language would be able to take advantage of Python's
                 inherently easy to understand syntax and Python ability
                 execute to itself, producing a neat integration of
                 program production and interpretation. However, Python
                 has the disadvantage that its execution speed is
                 relatively slow. This document details the
                 specification, design, and implementation for a Python
                 Grammatical framework and also documents the
                 experimental analysis of applying parallel computing
                 techniques in order to attempt to alleviate performance
                 issues as a result of using Python. It concludes that a
                 Python Grammatical Evolution framework is a valuable
                 tool, and that parallel computing techniques bring
                 performance gains in terms of both the execution speed
                 and the success rate of a Grammatical Evolution
  notes =        "Cited by \cite{Chennupati:2014:NaBIC}. Undergraduate
                 BSc. Bath University, UK",

Genetic Programming entries for Michael Stallard