Adding Program Length Bias to the Lexicase and Tournament Selection Algorithms

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@InProceedings{Moscovici:2016:GECCOcomp,
  author =       "Eva Moscovici",
  title =        "Adding Program Length Bias to the Lexicase and
                 Tournament Selection Algorithms",
  booktitle =    "GECCO '16 Companion: Proceedings of the Companion
                 Publication of the 2016 Annual Conference on Genetic
                 and Evolutionary Computation",
  year =         "2016",
  editor =       "Tobias Friedrich and Frank Neumann and 
                 Andrew M. Sutton and Martin Middendorf and Xiaodong Li and 
                 Emma Hart and Mengjie Zhang and Youhei Akimoto and 
                 Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and 
                 Daniele Loiacono and Julian Togelius and 
                 Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and 
                 Faustino Gomez and Carlos M. Fonseca and 
                 Heike Trautmann and Alberto Moraglio and William F. Punch and 
                 Krzysztof Krawiec and Zdenek Vasicek and 
                 Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and 
                 Boris Naujoks and Enrique Alba and Gabriela Ochoa and 
                 Simon Poulding and Dirk Sudholt and Timo Koetzing",
  isbn13 =       "978-1-4503-4323-7",
  pages =        "1035--1038",
  address =      "Denver, Colorado, USA",
  month =        "20-24 " # jul,
  keywords =     "genetic algorithms, genetic programming",
  organisation = "SIGEVO",
  DOI =          "doi:10.1145/2908961.2931668",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Lexicase selection is a relatively new but promising
                 algorithm for selecting parents to participate in
                 evolving the next generation of programs. Tournament
                 selection is a more established and commonly used
                 algorithm that serves the same purpose. As is the case
                 with many other genetic programming algorithms, the
                 programs generated with involvement of the lexicase and
                 tournament selection algorithms are often large and
                 hard to understand. There has been prior work done
                 related to parsimony and managing bloat in the programs
                 generated using genetic programming. In this paper, I
                 will discuss a way to reduce program size for lexicase
                 and tournament selection algorithms, by incorporating
                 the program length bias into the error for each test
                 case used to test whether an individual is fit enough
                 to participate in the evolution or not.",
  notes =        "Distributed at GECCO-2016.",
}

Genetic Programming entries for Eva Moscovici

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