Differentiable Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Izzo:2017:EuroGP,
  author =       "Dario Izzo and Francesco Biscani and Alessio Mereta",
  title =        "Differentiable Genetic Programming",
  booktitle =    "EuroGP 2017: Proceedings of the 20th European
                 Conference on Genetic Programming",
  year =         "2017",
  month =        "19-21 " # apr,
  editor =       "Mauro Castelli and James McDermott and 
                 Lukas Sekanina",
  series =       "LNCS",
  volume =       "10196",
  publisher =    "Springer Verlag",
  address =      "Amsterdam",
  pages =        "35--51",
  organisation = "species",
  note =         "Nominated for best paper",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1007/978-3-319-55696-3_3",
  abstract =     "We introduce the use of high order automatic
                 differentiation, implemented via the algebra of
                 truncated Taylor polynomials, in genetic programming.
                 Using the Cartesian Genetic Programming encoding we
                 obtain a high-order Taylor representation of the
                 program output that is then used to back-propagate
                 errors during learning. The resulting machine learning
                 framework is called differentiable Cartesian Genetic
                 Programming (dCGP). In the context of symbolic
                 regression, dCGP offers a new approach to the long
                 unsolved problem of constant representation in GP
                 expressions. On several problems of increasing
                 complexity we find that dCGP is able to find the exact
                 form of the symbolic expression as well as the
                 constants values. We also demonstrate the use of dCGP
                 to solve a large class of differential equations and to
                 find prime integrals of dynamical systems, presenting,
                 in both cases, results that confirm the efficacy of our
                 approach.",
  notes =        "see also https://arxiv.org/abs/1611.04766

                 Part of \cite{Castelli:2017:GP} EuroGP'2017 held
                 inconjunction with EvoCOP2017, EvoMusArt2017 and
                 EvoApplications2017",
}

Genetic Programming entries for Dario Izzo Francesco Biscani Alessio Mereta

Citations