The Uphill Battle of Ant Programming Vs. Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4215

  title =        "The Uphill Battle of Ant Programming Vs. Genetic
  author =       "Amirali Salehi-Abari and Tony White",
  year =         "2009",
  booktitle =    "International Conference on Evolutionary Computation
                 (ICEC 2009)",
  editor =       "Agostinho Rosa",
  pages =        "171--176",
  address =      "Madeira, Portugal",
  month =        "5-7 " # oct,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  size =         "6 pages",
  bibdate =      "2010-03-03",
  bibsource =    "DBLP,
  abstract =     "Ant programming has been proposed as an alternative to
                 Genetic Programming (GP) for the automated production
                 of computer programs. Generalized Ant Programming (GAP)
                 - an automated programming technique derived from
                 principles of swarm intelligence - has shown promise in
                 solving symbolic regression and other hard problems.
                 Enhanced Generalized Ant Programming (EGAP) has
                 improved upon the performance of GAP; however, a
                 comparison with GP has not been performed. This paper
                 compares EGAP and GP on 3 well-known tasks: Quartic
                 symbolic regression, multiplexer and an ant trail
                 problem. When comparing EGAP and GP, GP is found to be
                 statistically superior to EGAP. An analysis of the
                 evolving program populations shows that EGAP suffers
                 from premature diversity loss.",
  notes =        "broken

Genetic Programming entries for Amirali Salehi-Abari Tony White