Grammar-based immune programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Heder S. Bernardino and Helio J. C. Barbosa",
  title =        "Grammar-based immune programming",
  journal =      "Natural Computing",
  year =         "2011",
  volume =       "10",
  number =       "1",
  pages =        "209--241",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 evolution, Artificial immune system, AIS, Immune
                 programming, Symbolic regression, Model inference",
  ISSN =         "1567-7818",
  DOI =          "doi:10.1007/s11047-010-9217-x",
  abstract =     "This paper describes Grammar-based Immune Programming
                 (GIP) for evolving programs in an arbitrary language by
                 immunological inspiration. GIP is based on Grammatical
                 Evolution (GE) in which a grammar is used to define a
                 language and decode candidate solutions to a valid
                 representation (program). However, by default, GE uses
                 a Genetic Algorithm in the search process while GIP
                 uses an artificial immune system. Some modifications
                 are needed of an immune algorithm to use a grammar in
                 order to efficiently decode antibodies into programs.
                 Experiments are performed to analyse algorithm
                 behaviour over different aspects and compare it with
                 GEVA, a well known GE implementation. The methods are
                 applied to identify a causal model (an ordinary
                 differential equation) from an observed data set, to
                 symbolically regress an iterated function f(f(x)) =
                 g(x), and to find a symbolic representation of a
                 discontinuous function",
  language =     "English",

Genetic Programming entries for Heder Soares Bernardino Helio J C Barbosa