Prioritized grammar enumeration: symbolic regression by dynamic programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Worm:2013:GECCO,
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author = "Tony Worm and Kenneth Chiu",
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title = "Prioritized grammar enumeration: symbolic regression
by dynamic programming",
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booktitle = "GECCO '13: Proceeding of the fifteenth annual
conference on Genetic and evolutionary computation
conference",
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year = "2013",
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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",
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isbn13 = "978-1-4503-1963-8",
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pages = "1021--1028",
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month = "6-10 " # jul,
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organisation = "SIGEVO",
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address = "Amsterdam, The Netherlands",
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note = "Best paper",
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keywords = "genetic algorithms, genetic programming, PyPGE,
dynamic programming",
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DOI = "doi:10.1145/2463372.2463486",
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code_url = "https://github.com/verdverm/pypge",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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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.",
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notes = "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
Citations