Comparing the Performance of the Evolvable PiGrammatical Evolution Genotype-Phenotype Map to Grammatical Evolution in the Dynamic Ms. Pac-Man Environment
Created by W.Langdon from
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- @InProceedings{galvan-lopez_etal:cec2010,
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author = "Edgar Galvan-Lopez and David Fagan and Eoin Murphy and
John Mark Swafford and Alexandros Agapitos and
Michael O'Neill and Anthony Brabazon",
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title = "Comparing the Performance of the Evolvable
{PiGrammatical} Evolution Genotype-Phenotype Map to
Grammatical Evolution in the Dynamic {Ms. Pac-Man}
Environment",
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booktitle = "2010 IEEE World Congress on Computational
Intelligence",
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pages = "1587--1594",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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isbn13 = "978-1-4244-6910-9",
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DOI = "doi:10.1109/CEC.2010.5586508",
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abstract = "In this work, we examine the capabilities of two forms
of mappings by means of Grammatical Evolution (GE) to
successfully generate controllers by combining
high-level functions in a dynamic environment. In this
work we adopted the Ms. Pac-Man game as a benchmark
test bed. We show that the standard GE mapping and
Position Independent GE (piGE) mapping achieve similar
performance in terms of maximising the score. We also
show that the controllers produced by both approaches
have an overall better performance in terms of
maximising the score compared to a hand-coded agent.
There are, however, significant differences in the
controllers produced by these two approaches: standard
GE produces more controllers with invalid code, whereas
the opposite is seen with piGE.",
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notes = "WCCI 2010. Also known as \cite{5586508}",
- }
Genetic Programming entries for
Edgar Galvan Lopez
David Fagan
Eoin Murphy
John Mark Swafford
Alexandros Agapitos
Michael O'Neill
Anthony Brabazon
Citations