Implicit Bias in Grammar-based Estimation of Distribution Genetic Programming: The Effects of Recursive Structure
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Kim:2012:CEC,
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title = "Implicit Bias in Grammar-based Estimation of
Distribution Genetic Programming: The Effects of
Recursive Structure",
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author = "Kangil Kim and Bob (R. I) McKay and
{Nguyen Xuan Hoai}",
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pages = "2373--2380",
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booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary
Computation",
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year = "2012",
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editor = "Xiaodong Li",
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month = "10-15 " # jun,
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DOI = "doi:10.1109/CEC.2012.6256565",
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address = "Brisbane, Australia",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Estimation of
distribution algorithms, Evolutionary computation
theory",
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abstract = "Much recent research in Estimation of Distribution
Algorithms (EDA) applied to Genetic Programming has
adopted a Stochastic Context Free Grammar(SCFG)-based
model formalism. However these methods generate biases
which may be indistinguishable from selection bias,
resulting in sub-optimal performance. The primary
factor generating this bias is the combined effect of
recursion in the grammars and depth limitation removing
some sample trees from the distribution. Here, we
demonstrate the bias and provide exact estimates of its
scale (assuming infinite populations and simple
recursions). We define a quantity h which determines
both whether bias occurs (h > 1) and its scale. We
apply this analysis to a number of simple illustrative
grammars, and to a range of practically-used GP
grammars, showing that this bias is both real and
important.",
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notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
EPS and the IET.",
- }
Genetic Programming entries for
Kangil Kim
R I (Bob) McKay
Nguyen Xuan Hoai
Citations