Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Created by W.Langdon from
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- @Article{Silva:2012:GPEM,
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author = "Sara Silva and Stephen Dignum and Leonardo Vanneschi",
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title = "Operator equalisation for bloat free genetic
programming and a survey of bloat control methods",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2012",
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volume = "13",
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number = "2",
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pages = "197--238",
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month = jun,
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keywords = "genetic algorithms, genetic programming, Bloat,
Crossover bias, Operator equalisation, Review, Bloat
control methods",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-011-9150-5",
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size = "42 pages",
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abstract = "Bloat can be defined as an excess of code growth
without a corresponding improvement in fitness. This
problem has been one of the most intensively studied
subjects since the beginnings of Genetic Programming.
This paper begins by briefly reviewing the theories
explaining bloat, and presenting a comprehensive survey
and taxonomy of many of the bloat control methods
published in the literature through the years.
Particular attention is then given to the new Crossover
Bias theory and the bloat control method it inspired,
Operator Equalisation (OpEq). Two implementations of
OpEq are described in detail. The results presented
clearly show that Genetic Programming using OpEq is
essentially bloat free. We discuss the advantages and
shortcomings of each different implementation, and the
unexpected effect of OpEq on overfitting. We observe
the evolutionary dynamics of OpEq and address its
potential to be extended and integrated into different
elements of the evolutionary process.",
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affiliation = "INESC-ID Lisboa, Rua Alves Redol 9, 1000-029 Lisboa,
Portugal",
- }
Genetic Programming entries for
Sara Silva
Stephen Dignum
Leonardo Vanneschi
Citations