Parameter sweeps for exploring GP parameters

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

@InProceedings{1068313,
  author =       "Michael E. Samples and Jason M. Daida and 
                 Matthew Byom and Matt Pizzimenti",
  title =        "Parameter sweeps for exploring GP parameters",
  booktitle =    "{GECCO 2005}: Proceedings of the 2005 conference on
                 Genetic and evolutionary computation",
  year =         "2005",
  editor =       "Hans-Georg Beyer and Una-May O'Reilly and 
                 Dirk V. Arnold and Wolfgang Banzhaf and Christian Blum and 
                 Eric W. Bonabeau and Erick Cantu-Paz and 
                 Dipankar Dasgupta and Kalyanmoy Deb and James A. Foster and 
                 Edwin D. {de Jong} and Hod Lipson and Xavier Llora and 
                 Spiros Mancoridis and Martin Pelikan and Guenther R. Raidl and 
                 Terence Soule and Andy M. Tyrrell and 
                 Jean-Paul Watson and Eckart Zitzler",
  volume =       "2",
  ISBN =         "1-59593-010-8",
  pages =        "1791--1792",
  address =      "Washington DC, USA",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005/docs/p1791.pdf",
  DOI =          "doi:10.1145/1068009.1068313",
  publisher =    "ACM Press",
  publisher_address = "New York, NY, 10286-1405, USA",
  month =        "25-29 " # jun,
  organisation = "ACM SIGEVO (formerly ISGEC)",
  keywords =     "genetic algorithms, genetic programming, Poster,
                 evolutionary computation, data reduction, distributed
                 computation, experiment management, experimentation,
                 parameter sweep, performance, SVN",
  size =         "8 pages",
  abstract =     "This paper describes our procedure and a software
                 application for conducting large parameter sweep
                 experiments in genetic and evolutionary computation
                 research. Both procedure and software allows a
                 researcher to examine multivariate nonlinearities that
                 are common in genetic and evolutionary computation.
                 Experiments of this nature are well suited to
                 distributed computing environments (such as Grids and
                 clusters) and we present an automated system for
                 conducting parameter sweep experiments on heterogeneous
                 networks. Emphasis is placed on experimental sampling,
                 distributed robustness, and data analysis. The
                 parameter sweep experimental procedure is easily
                 applicable to any experiment involving computer
                 simulations but is particularly well suited for
                 evolutionary computation experiments. Categories and
                 Subject Descriptors",
  notes =        "GECCO-2005 A joint meeting of the fourteenth
                 international conference on genetic algorithms
                 (ICGA-2005) and the tenth annual genetic programming
                 conference (GP-2005).

                 ACM Order Number 910052

                 Commander architectural and processes diagram showing
                 Host, Client, and Subversion server.",
}

Genetic Programming entries for Michael E Samples Jason M Daida Matthew J Byom Matt Pizzimenti

Citations