Comparison of Semantic-aware Selection Methods in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7989
- @InProceedings{Liskowski:2015:GECCOcomp,
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author = "Pawel Liskowski and Krzysztof Krawiec and
Thomas Helmuth and Lee Spector",
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title = "Comparison of Semantic-aware Selection Methods in
Genetic Programming",
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booktitle = "GECCO 2015 Semantic Methods in Genetic Programming
(SMGP'15) Workshop",
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year = "2015",
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editor = "Colin Johnson and Krzysztof Krawiec and
Alberto Moraglio and Michael O'Neill",
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isbn13 = "978-1-4503-3488-4",
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keywords = "genetic algorithms, genetic programming, Semantic
Methods in (SMGP'15) Workshop",
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pages = "1301--1307",
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month = "11-15 " # jul,
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organisation = "SIGEVO",
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address = "Madrid, Spain",
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URL = "http://doi.acm.org/10.1145/2739482.2768505",
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DOI = "doi:10.1145/2739482.2768505",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "This study investigates the performance of several
semantic-aware selection methods for genetic
programming (GP). In particular, we consider methods
that do not rely on complete GP semantics (i.e., a
tuple of outputs produced by a program for fitness
cases (tests)), but on binary outcome vectors that only
state whether a given test has been passed by a program
or not. This allows us to relate to test-based problems
commonly considered in the domain of coevolutionary
algorithms and, in prospect, to address a wider range
of practical problems, in particular the problems where
desired program output is unknown (e.g., evolving GP
controllers). The selection methods considered in the
paper include implicit fitness sharing (ifs), discovery
of derived objectives (doc), lexicase selection (lex),
as well as a hybrid of the latter two. These
techniques, together with a few variants, are
experimentally compared to each other and to
conventional GP on a battery of discrete benchmark
problems. The outcomes indicate superior performance of
lex and ifs, with some variants of doc showing certain
potential.",
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notes = "Also known as \cite{2768505} Distributed at
GECCO-2015.",
- }
Genetic Programming entries for
Pawel Liskowski
Krzysztof Krawiec
Thomas Helmuth
Lee Spector
Citations