Complexity Drift in Evolutionary Computation with Tree Representations
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @TechReport{rosca:1996:cdectr,
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author = "Justinian P. Rosca and Dana H. Ballard",
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title = "Complexity Drift in Evolutionary Computation with Tree
Representations",
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institution = "University of Rochester, Computer Science Department",
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year = "1996",
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type = "Technical Report",
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number = "NRL5",
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address = "Rochester, NY, USA",
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month = dec,
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keywords = "genetic algorithms, genetic programming",
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URL = "ftp://ftp.cs.rochester.edu/pub/u/rosca/gp/96.drift.ps.gz",
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abstract = "One serious problem of standard Genetic Programming
(GP) is that evolved expressions appear to drift
towards large and slow forms on average. This report
presents a novel analysis of the role played by
variable complexity in the selection and survival of GP
expressions. It defines a particular property of GP
representations, called {\it rooted tree-schema}, that
sheds light on the role of variable complexity of
evolved representations. A tree-schema is a relation on
the space of tree-shaped structures which provides a
quantifiable partitioning of the search space. The
present analysis answers questions such as: What role
does variable complexity play in the selection and
survival of evolved expressions? What is the influence
of a parsimony penalty? How heavy should parsimony
penalty be weighted or how should it be adapted in
order to preserve the underlying optimization process?
Are there alternative approaches to simulating a
parsimony penalty that do not result in a change of the
fitness landscape? The present report provides
theoretical answers to these questions, interpretation
of these results, and an experimental perspective.",
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notes = "Section 2 Schemata Theory",
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size = "30 pages",
- }
Genetic Programming entries for
Justinian Rosca
Dana H Ballard
Citations