Implicit Bias in Grammar-based Estimation of Distribution Genetic Programming: The Effects of Recursive Structure

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@InProceedings{Kim:2012:CEC,

• title = "Implicit Bias in Grammar-based Estimation of Distribution Genetic Programming: The Effects of Recursive Structure",
• author = "Kangil Kim and Bob (R. I) McKay and {Nguyen Xuan Hoai}",
• pages = "2373--2380",
• booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary Computation",
• year = "2012",
• editor = "Xiaodong Li",
• month = "10-15 " # jun,
• DOI = "doi:10.1109/CEC.2012.6256565",
• address = "Brisbane, Australia",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Estimation of distribution algorithms, Evolutionary computation theory",
• 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.",
• 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