Genetic Algorithms and Programming-An Evolutionary Methodology
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Misc{Venkat:2010:IJHIT,
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title = "Genetic Algorithms and Programming-An Evolutionary
Methodology",
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author = "T. Venkat Narayana Rao and Srikanth Madiraju",
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journal = "International Journal of Hybrid Information
Technology",
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year = "2010",
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volume = "3",
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number = "4",
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month = oct,
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keywords = "genetic algorithms, genetic programming, subtree,
chromosomes, mutation",
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annote = "The Pennsylvania State University CiteSeerX Archives",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.303.8499",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.303.8499",
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URL = "http://www.sersc.org/journals/IJHIT/vol3_no4_2010/1.pdf",
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abstract = "Genetic programming (GP) is an automated method for
creating a working computer program from a high-level
problem statement of a problem. Genetic programming
starts from a high-level statement of what needs to be
done and automatically creates a computer program to
solve the problem. In artificial intelligence, genetic
programming (GP) is an evolutionary algorithm-based
methodology inspired by biological evolution to find
computer programs that perform a user defined task. It
is a specialisation of genetic algorithms (GA) where
each individual is a computer program. It is a machine
learning technique used to optimise a population of
computer programs according to a fitness span
determined by a program{'}s ability to perform a given
computational task. This paper presents a idea of the
various principles of genetic programming which
includes, relative effectiveness of mutation,
crossover, breeding computer programs and fitness test
in genetic programming. The literature of traditional
genetic algorithms contains related studies, but
through GP, it saves time by freeing the human from
having to design complex algorithms. Not only designing
the algorithms but creating ones that give optimal
solutions than traditional counterparts in noteworthy
ways.",
- }
Genetic Programming entries for
T Venkat Narayana Rao
Srikanth Madiraju
Citations