Prioritized grammar enumeration: symbolic regression by dynamic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Tony Worm and Kenneth Chiu",
  title =        "Prioritized grammar enumeration: symbolic regression
                 by dynamic programming",
  booktitle =    "GECCO '13: Proceeding of the fifteenth annual
                 conference on Genetic and evolutionary computation
  year =         "2013",
  editor =       "Christian Blum and Enrique Alba and Anne Auger and 
                 Jaume Bacardit and Josh Bongard and Juergen Branke and 
                 Nicolas Bredeche and Dimo Brockhoff and 
                 Francisco Chicano and Alan Dorin and Rene Doursat and 
                 Aniko Ekart and Tobias Friedrich and Mario Giacobini and 
                 Mark Harman and Hitoshi Iba and Christian Igel and 
                 Thomas Jansen and Tim Kovacs and Taras Kowaliw and 
                 Manuel Lopez-Ibanez and Jose A. Lozano and Gabriel Luque and 
                 John McCall and Alberto Moraglio and 
                 Alison Motsinger-Reif and Frank Neumann and Gabriela Ochoa and 
                 Gustavo Olague and Yew-Soon Ong and 
                 Michael E. Palmer and Gisele Lobo Pappa and 
                 Konstantinos E. Parsopoulos and Thomas Schmickl and Stephen L. Smith and 
                 Christine Solnon and Thomas Stuetzle and El-Ghazali Talbi and 
                 Daniel Tauritz and Leonardo Vanneschi",
  isbn13 =       "978-1-4503-1963-8",
  pages =        "1021--1028",
  keywords =     "genetic algorithms, genetic programming, dynamic
  month =        "6-10 " # jul,
  organisation = "SIGEVO",
  address =      "Amsterdam, The Netherlands",
  DOI =          "doi:10.1145/2463372.2463486",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "We introduce Prioritised Grammar Enumeration (PGE), a
                 deterministic Symbolic Regression (SR) algorithm using
                 dynamic programming techniques. PGE maintains the
                 tree-based representation and Pareto non-dominated
                 sorting from Genetic Programming (GP), but replaces
                 genetic operators and random number use with grammar
                 production rules and systematic choices. PGE uses
                 non-linear regression and abstract parameters to fit
                 the coefficients of an equation, effectively separating
                 the exploration for form, from the optimisation of a
                 form. Memoisation enables PGE to evaluate each point of
                 the search space only once, and a Pareto Priority Queue
                 provides direction to the search. Sorting and
                 simplification algorithms are used to transform
                 candidate expressions into a canonical form, reducing
                 the size of the search space. Our results show that PGE
                 performs well on 22 benchmarks from the SR literature,
                 returning exact formulae in many cases. As a
                 deterministic algorithm, PGE offers reliability and
                 reproducibility of results, a key aspect to any system
                 used by scientists at large. We believe PGE is a
                 capable SR implementation, following an alternative
                 perspective we hope leads the community to new ideas.",
  notes =        "Best paper.

                 Also known as \cite{2463486} GECCO-2013 A joint meeting
                 of the twenty second international conference on
                 genetic algorithms (ICGA-2013) and the eighteenth
                 annual genetic programming conference (GP-2013)",

Genetic Programming entries for Tony Worm Kenneth Chiu