Computational Complexity Analysis of Simple Genetic Programming On Two Problems Modeling Isolated Program Semantics
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Durrett:2011:foga,
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author = "Greg Durrett and Frank Neumann and Una-May O'Reilly",
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title = "Computational Complexity Analysis of Simple Genetic
Programming On Two Problems Modeling Isolated Program
Semantics",
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booktitle = "Foundations of Genetic Algorithms",
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year = "2011",
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editor = "Hans-Georg Beyer and W. B. Langdon",
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pages = "69--80",
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address = "Schwarzenberg, Austria",
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month = "5-9 " # jan,
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organisation = "SigEvo",
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publisher = "ACM",
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keywords = "genetic algorithms, genetic programming, Genetic
Programming Theory, Computational Complexity, Hill
Climbing",
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isbn13 = "978-1-4503-0633-1",
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DOI = "doi:10.1145/1967654.1967661",
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size = "12 pages",
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abstract = "Analysing the computational complexity of evolutionary
algorithms (EAs) for binary search spaces has
significantly informed our understanding of EAs in
general. With this paper, we start the computational
complexity analysis of genetic programming (GP). We set
up several simplified GP algorithms and analyse them on
two separable model problems, ORDER and MAJORITY, each
of which captures a relevant facet of typical GP
problems. Both analyses give first rigorous insights
into aspects of GP design, highlighting in particular
the impact of accepting or rejecting neutral moves and
the importance of a local mutation operator.",
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notes = "See \cite{Durrett:2010:ccaGP2pmips}
\cite{Nguyen:2013:foga} FOGA11 ACM order number
910114",
- }
Genetic Programming entries for
Greg Durrett
Frank Neumann
Una-May O'Reilly
Citations