Word count as a traditional programming benchmark problem for genetic programming

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

@InProceedings{Helmuth:2014:GECCO,
  author =       "Thomas Helmuth and Lee Spector",
  title =        "Word count as a traditional programming benchmark
                 problem for genetic programming",
  booktitle =    "GECCO '14: Proceedings of the 2014 conference on
                 Genetic and evolutionary computation",
  year =         "2014",
  editor =       "Christian Igel and Dirk V. Arnold and 
                 Christian Gagne and Elena Popovici and Anne Auger and 
                 Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and 
                 Kalyanmoy Deb and Benjamin Doerr and James Foster and 
                 Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and 
                 Hitoshi Iba and Christian Jacob and Thomas Jansen and 
                 Yaochu Jin and Marouane Kessentini and 
                 Joshua D. Knowles and William B. Langdon and Pedro Larranaga and 
                 Sean Luke and Gabriel Luque and John A. W. McCall and 
                 Marco A. {Montes de Oca} and Alison Motsinger-Reif and 
                 Yew Soon Ong and Michael Palmer and 
                 Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and 
                 Guenther Ruhe and Tom Schaul and Thomas Schmickl and 
                 Bernhard Sendhoff and Kenneth O. Stanley and 
                 Thomas Stuetzle and Dirk Thierens and Julian Togelius and 
                 Carsten Witt and Christine Zarges",
  isbn13 =       "978-1-4503-2662-9",
  pages =        "919--926",
  keywords =     "genetic algorithms, genetic programming",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Vancouver, BC, Canada",
  URL =          "http://doi.acm.org/10.1145/2576768.2598230",
  DOI =          "doi:10.1145/2576768.2598230",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "The Unix utility program wc, which stands for word
                 count, takes any number of files and prints the number
                 of newlines, words, and characters in each of the
                 files. We show that genetic programming can find
                 programs that replicate the core functionality of the
                 wc utility, and propose this problem as a traditional
                 programming benchmark for genetic programming systems.
                 This wc problem features key elements of programming
                 tasks that often confront human programmers, including
                 requirements for multiple data types, a large
                 instruction set, control flow, and multiple outputs.
                 Furthermore, it mimics the behavior of a real-world
                 utility program, showing that genetic programming can
                 automatically synthesize programs with general utility.
                 We suggest statistical procedures that should be used
                 to compare performances of different systems on
                 traditional programming problems such as the wc
                 problem, and present the results of a short experiment
                 using the problem. Finally, we give a short analysis of
                 evolved solution programs, showing how they make use of
                 traditional programming concepts.",
  notes =        "Also known as \cite{2598230} GECCO-2014 A joint
                 meeting of the twenty third international conference on
                 genetic algorithms (ICGA-2014) and the nineteenth
                 annual genetic programming conference (GP-2014)",
}

Genetic Programming entries for Thomas Helmuth Lee Spector

Citations