Genetic Programming Bloat with Dynamic Fitness

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

@TechReport{langdon:1997:dynbloatTR,
  author =       "W. B. Langdon and R. Poli",
  title =        "Genetic Programming Bloat with Dynamic Fitness",
  institution =  "University of Birmingham, School of Computer Science",
  number =       "CSRP-97-29",
  month =        "3 " # dec,
  year =         "1997",
  keywords =     "genetic algorithms, genetic programming",
  file =         "/1997/CSRP-97-29.ps.gz",
  URL =          "ftp://ftp.cs.bham.ac.uk/pub/tech-reports/1997/CSRP-97-29.ps.gz",
  abstract =     "In artificial evolution individuals which perform as
                 their parents are usually rewarded identically to their
                 parents. We note that Nature is more dynamic and there
                 may be a penalty to pay for doing the same thing as
                 your parents. We report two sets of experiments where
                 static fitness functions are firstly augmented by a
                 penalty for unchanged offspring and secondly the static
                 fitness case is replaced by randomly generated dynamic
                 test cases. We conclude genetic programming, when
                 evolving artificial ant control programs, is
                 surprisingly little effected by large penalties and
                 program growth is observed in all our experiments.",
}

Genetic Programming entries for William B Langdon Riccardo Poli

Citations