Contribution based bloat control in Genetic Programming

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  author =       "Andy Song and Dunhai Chen and Mengjie Zhang",
  title =        "Contribution based bloat control in Genetic
  booktitle =    "IEEE Congress on Evolutionary Computation (CEC 2010)",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4244-6910-9",
  abstract =     "Unnecessary growth in program size is known as the
                 bloat problem in Genetic Programming. Bloat not only
                 increases computational expenses during evolution, but
                 also impairs the understandability and execution
                 performance of evolved final solutions. There are a
                 large number of studies addressing this problem. In
                 this paper, we present an effective bloat control
                 mechanism which is based on examining the contribution
                 of each function node in the selected programs. Nodes
                 without contribution will be removed before generating
                 offspring. This method has been applied to various
                 tasks. The results show that it can significantly
                 reduce program size without damping the fitness of
                 individuals. In some cases it increases the performance
                 of the final solutions. Furthermore it does not require
                 extra computational resources to perform the control
                 whilst it speeds up evolution processes because of the
                 saving in evaluation costs.",
  DOI =          "doi:10.1109/CEC.2010.5586372",
  notes =        "WCCI 2010. Also known as \cite{5586372}",

Genetic Programming entries for Andy Song Dunhai Chen Mengjie Zhang