Prioritized grammar enumeration: symbolic regression by dynamic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Worm:2013:GECCO,

• 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 conference",
• 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",
• month = "6-10 " # jul,
• organisation = "SIGEVO",
• address = "Amsterdam, The Netherlands",
• note = "Best paper",
• keywords = "genetic algorithms, genetic programming, PyPGE, dynamic programming",
• DOI = "doi:10.1145/2463372.2463486",
• code_url = "https://github.com/verdverm/pypge",
• 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 = "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