An effective parse tree representation for tartarus
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gp-bibliography.bib Revision:1.8051
- @InProceedings{Dick:2013:GECCOa,
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author = "Grant Dick",
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title = "An effective parse tree representation for tartarus",
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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 = "909--916",
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keywords = "genetic algorithms, genetic programming",
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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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DOI = "doi:10.1145/2463372.2463497",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "Recent work in genetic programming (GP) has
highlighted the need for stronger benchmark problems.
For benchmarking planning scenarios, the artificial ant
problem is often used. With a limited number of test
cases, this problem is often fairly simple to solve. A
more complex planning problem is Tartarus, but as of
yet no standard representation for Tartarus exists for
GP. This paper examines an existing parse tree
representation for Tartarus, and identifies weaknesses
in the way in which it manipulates environmental
information. Through this analysis, an alternative
representation is proposed for Tartarus that shares
many similarities with those already used in GP for
planning problems. Empirical analysis suggests that the
proposed representation has qualities that make it a
suitable benchmark problem.",
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notes = "Also known as \cite{2463497} 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
Grant Dick
Citations