Recurrent Cartesian Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Turner:2014:PPSN,
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author = "Andrew Turner and Julian Miller",
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title = "Recurrent Cartesian Genetic Programming",
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booktitle = "13th International Conference on Parallel Problem
Solving from Nature",
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year = "2014",
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editor = "Thomas Bartz-Beielstein and Juergen Branke and
Bogdan Filipic and Jim Smith",
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publisher = "Springer",
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isbn13 = "978-3-319-10761-5",
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pages = "476--486",
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series = "Lecture Notes in Computer Science",
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address = "Ljubljana, Slovenia",
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month = "13-17 " # sep,
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volume = "8672",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1007/978-3-319-10762-2_47",
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abstract = "This paper formally introduces Recurrent Cartesian
Genetic Programming (RCGP), an extension to Cartesian
Genetic Programming (CGP) which allows recurrent
connections. The presence of recurrent connections
enables RCGP to be successfully applied to partially
observable tasks. It is found that RCGP significantly
outperforms CGP on two partially observable tasks:
artificial ant and sunspot prediction. The paper also
introduces a new parameter, recurrent connection
probability, which biases the number of recurrent
connections created via mutation. Suitable choices of
this parameter significantly improve the effectiveness
of RCGP.",
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notes = "PPSN-XIII",
- }
Genetic Programming entries for
Andrew James Turner
Julian F Miller
Citations