Evolution of an Effective Brain-Computer Interface Mouse via Genetic Programming with Adaptive Tarpeian Bloat Control

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

@InCollection{Poli:2011:GPTP,
  author =       "Riccardo Poli and Mathew Salvaris and Caterina Cinel",
  title =        "Evolution of an Effective Brain-Computer Interface
                 Mouse via Genetic Programming with Adaptive Tarpeian
                 Bloat Control",
  booktitle =    "Genetic Programming Theory and Practice IX",
  year =         "2011",
  editor =       "Rick Riolo and Ekaterina Vladislavleva and 
                 Jason H. Moore",
  series =       "Genetic and Evolutionary Computation",
  address =      "Ann Arbor, USA",
  month =        "12-14 " # may,
  publisher =    "Springer",
  chapter =      "5",
  pages =        "77--95",
  keywords =     "genetic algorithms, genetic programming, Brain
                 Computer Interfaces, Adaptive Tarpeian method, Bloat
                 control",
  isbn13 =       "978-1-4614-1769-9",
  DOI =          "doi:10.1007/978-1-4614-1770-5_5",
  abstract =     "The Tarpeian method for bloat control has been shown
                 to be a robust technique to control bloat. The
                 covariant Tarpeian method introduced last year, solves
                 the problem of optimally setting the parameters of the
                 method so as to achieve full control over the dynamics
                 of mean program size. However, the theory supporting
                 such a technique is applicable only in the case of
                 fitness proportional selection and for a generational
                 system with crossover only. we propose an adaptive
                 variant of the Tarpeian method, which does not suffer
                 from this limitation. The method automatically adjusts
                 the rate of application of Tarpeian bloat control so as
                 to achieve a desired program size dynamics. We test the
                 method in a variety of standard benchmark problems as
                 well as in a real-world application in the field of
                 Brain Computer Interfaces, obtaining excellent
                 results.",
  notes =        "part of \cite{Riolo:2011:GPTP}",
  affiliation =  "School of Computer Science and Electronic Engineering,
                 University of Essex, Wivenhoe Park, CO4 3SQ UK",
}

Genetic Programming entries for Riccardo Poli Mathew Salvaris Caterina Cinel

Citations