Genetic Programming Bloat with Dynamic Fitness

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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