A new genetic programming framework based on reaction systems

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@Article{Manzoni:2013:GPEM,
  author =       "Luca Manzoni and Mauro Castelli and 
                 Leonardo Vanneschi",
  title =        "A new genetic programming framework based on reaction
                 systems",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2013",
  volume =       "14",
  number =       "4",
  pages =        "457--471",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, Reaction
                 systems, Evolutionary computation",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-013-9184-y",
  size =         "15 pages",
  abstract =     "This paper presents a new genetic programming
                 framework called Evolutionary Reaction Systems. It is
                 based on a recently defined computational formalism,
                 inspired by chemical reactions, called Reaction
                 Systems, and it has several properties that distinguish
                 it from other existing genetic programming frameworks,
                 making it interesting and worthy of investigation. For
                 instance, it allows us to express complex constructs in
                 a simple and intuitive way, and it lightens the final
                 user from the task of defining the set of primitive
                 functions used to build up the evolved programs. Given
                 that Evolutionary Reaction Systems is new and it has
                 small similarities with other existing genetic
                 programming frameworks, a first phase of this work is
                 dedicated to a study of some important parameters and
                 their influence on the algorithm's performance.
                 Successively, we use the best parameter setting found
                 to compare Evolutionary Reaction Systems with other
                 well established machine learning methods, including
                 standard tree-based genetic programming. The presented
                 results show that Evolutionary Reaction Systems are
                 competitive with, and in some cases even better than,
                 the other studied methods on a wide set of
                 benchmarks.",
}

Genetic Programming entries for Luca Manzoni Mauro Castelli Leonardo Vanneschi

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