Causality in Genetic Programming
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gp-bibliography.bib Revision:1.7964
- @InProceedings{Rosca:1995:cause,
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author = "Justinian Rosca and Dana H. Ballard",
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title = "Causality in Genetic Programming",
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booktitle = "Genetic Algorithms: Proceedings of the Sixth
International Conference (ICGA95)",
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year = "1995",
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editor = "Larry J. Eshelman",
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pages = "256--263",
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address = "Pittsburgh, PA, USA",
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publisher_address = "San Francisco, CA, USA",
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month = "15-19 " # jul,
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publisher = "Morgan Kaufmann",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-55860-370-0",
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URL = "ftp://ftp.cs.rochester.edu/pub/u/rosca/gp/95.icga.causality.ps.gz",
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size = "8 pages",
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abstract = "Causality relates changes in the structure of an
object with the effects of such changes, that is
changes in the properties or behavior of the object.
This paper analyzes the concept of causality in Genetic
Programming (GP) and suggests how it can be used in
adapting control parameters for speeding up GP search.
We first analyze the effects of crossover to show the
weak causality of the GP representation and operators.
Hierarchical GP approaches based on the discovery and
evolution of functions amplify this phenomenon.
However, selection gradually retains strongly causal
changes. Causality is correlated to search space
exploitation and is discussed in the context of the
exploration-exploitation tradeoff. The results
described argue for a bottom-up GP evolutionary thesis.
Finally, new developments based on the idea of GP
architecture evolution [Koza94] are discussed from the
causality perspective.",
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notes = "\cite{Rosca:1995:aHGP} is a longer version of this
paper",
- }
Genetic Programming entries for
Justinian Rosca
Dana H Ballard
Citations