Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression
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- @InProceedings{Burlacu:2019:EUROCAST,
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author = "Bogdan Burlacu and Lukas Kammerer and
Michael Affenzeller and Gabriel Kronberger",
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title = "Hash-Based Tree Similarity and Simplification in
Genetic Programming for Symbolic Regression",
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booktitle = "International Conference on Computer Aided Systems
Theory, EUROCAST 2019",
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year = "2019",
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editor = "Roberto Moreno-Diaz and Franz Pichler and
Alexis Quesada-Arencibia",
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volume = "12013",
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series = "Lecture Notes in Computer Science",
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pages = "361--369",
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address = "Las Palmas de Gran Canaria, Spain",
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month = "17-22 " # feb,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-030-45092-2",
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DOI = "doi:10.1007/978-3-030-45093-9_44",
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abstract = "We introduce in this paper a runtime-efficient tree
hashing algorithm for the identification of isomorphic
subtrees, with two important applications in genetic
programming for symbolic regression: fast, online
calculation of population diversity and algebraic
simplification of symbolic expression trees. Based on
this hashing approach, we propose a simple
diversity-preservation mechanism with promising results
on a collection of symbolic regression benchmark
problems.",
- }
Genetic Programming entries for
Bogdan Burlacu
Lukas Kammerer
Michael Affenzeller
Gabriel Kronberger
Citations