Combining semantically-effective and geometric crossover operators for Genetic Programming
Created by W.Langdon from
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- @InProceedings{Pawlak:2014:PPSN,
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author = "Tomasz Pawlak",
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title = "Combining semantically-effective and geometric
crossover operators for Genetic Programming",
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booktitle = "13th International Conference on Parallel Problem
Solving from Nature",
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year = "2014",
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editor = "Thomas Bartz-Beielstein and Juergen Branke and
Bogdan Filipic and Jim Smith",
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publisher = "Springer",
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isbn13 = "978-3-319-10761-5",
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pages = "454--464",
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series = "Lecture Notes in Computer Science",
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address = "Ljubljana, Slovenia",
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month = "13-17 " # sep,
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volume = "8672",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1007/978-3-319-10762-2_45",
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abstract = "We propose a way to combine two distinct general
patterns for designing semantic crossover operators for
genetic programming: geometric semantic approach and
semantically-effective approach. In the experimental
part we show the synergistic effects of combining these
two approaches, which we explain by a major fraction of
crossover acts performed by geometric semantic
crossover operators being semantically ineffective. The
results of the combined approach show significant
improvement of performance and high resistance to a
premature convergence.",
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notes = "PPSN-XIII",
- }
Genetic Programming entries for
Tomasz Pawlak
Citations