Local Search is Underused in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Trujillo:2016:GPTP,
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title = "Local Search is Underused in Genetic Programming",
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author = "Leonardo Trujillo and Emigdio Z-Flores and
Perla S. {Juarez Smith} and Pierrick Legrand and Sara Silva and
Mauro Castelli and Leonardo Vanneschi and
Oliver Schuetze and Luiz Munoz",
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booktitle = "Genetic Programming Theory and Practice XIV",
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year = "2016",
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editor = "William Tozier and Brian W. Goldman and
Bill Worzel and Rick Riolo",
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series = "Genetic and Evolutionary Computation",
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pages = "119--137",
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address = "Ann Arbor, USA",
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month = "19-21 " # may,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Local Search,
Bloat, NEAT",
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hal_id = "hal-01388426",
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hal_version = "v1",
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isbn13 = "978-3-319-97087-5",
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URL = "https://hal.inria.fr/hal-01388426",
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URL = "https://www.researchgate.net/publication/312016495_Local_Search_is_Underused_in_Genetic_Programming",
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URL = "https://www.springer.com/us/book/9783319970875",
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size = "18 pages",
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abstract = "There are two important limitations of standard
tree-based genetic programming (GP). First, GP tends to
evolve unnecessarily large programs, what is referred
to as bloat. Second, GP uses inefficient search
operators that focus on modifying program syntax. The
first problem has been studied in many works, with many
bloat control proposals. Regarding the second problem,
one approach is to use alternative search operators,
for instance geometric semantic operators, to improve
convergence. In this work, our goal is to
experimentally show that both problems can be
effectively addressed by incorporating a local search
optimizer as an additional search operator. Using
real-world problems, we show that this rather simple
strategy can improve the convergence and performance of
tree-based GP, while reducing program size. Given these
results, a question arises: why are local search
strategies so uncommon in GP? A small survey of popular
GP libraries suggests to us that local search is
underused in GP systems. We conclude by outlining
plausible answers for this question and highlighting
future work.",
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notes = "also known as \cite{leonardo:hal-01388426}
Instituto Tecnologico de Tijuana, Mexico
Part of \cite{Tozier:2016:GPTP} published after the
workshop",
- }
Genetic Programming entries for
Leonardo Trujillo
Emigdio Z-Flores
Perla Sarahi Juarez-Smith
Pierrick Legrand
Sara Silva
Mauro Castelli
Leonardo Vanneschi
Oliver Schuetze
Luis Munoz Delgado
Citations