Genetic Programming: Introduction, Applications, Theory and Open Issues
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InCollection{VanneschiPoliHNC2011,
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author = "Leonardo Vanneschi and Riccardo Poli",
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title = "Genetic Programming: Introduction, Applications,
Theory and Open Issues",
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booktitle = "Handbook of Natural Computing",
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publisher = "Springer",
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year = "2012",
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editor = "Grzegorz Rozenberg and Thomas Baeck and Joost N. Kok",
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volume = "2",
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chapter = "24",
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pages = "709--739",
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month = "19 " # aug,
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-540-92909-3",
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URL = "http://cswww.essex.ac.uk/staff/poli/papers/VanneschiPoliHNC2011.pdf",
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URL = "http://www.springer.com/computer/theoretical+computer+science/book/978-3-540-92911-6",
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DOI = "doi:10.1007/978-3-540-92910-9_24",
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abstract = "Genetic programming (GP) is an evolutionary approach
that extends genetic algorithms to allow the
exploration of the space of computer programs. Like
other evolutionary algorithms, GP works by defining a
goal in the form of a quality criterion (or fitness)
and then using this criterion to evolve a set (or
population) of candidate solutions (individuals) by
mimicking the basic principles of Darwinian evolution.
GP breeds the solutions to problems using an iterative
process involving the probabilistic selection of the
fittest solutions and their variation by means of a set
of genetic operators, usually crossover and mutation.
GP has been successfully applied to a number of
challenging real-world problem domains. Its operations
and behaviour are now reasonably well understood thanks
to a variety of powerful theoretical results. In this
chapter, the main definitions and features of GP are
introduced and its typical operations are described.
Some of its applications are then surveyed. Some
important theoretical results in this field, including
some very recent ones, are reviewed and some of the
most challenging open issues and directions for future
research are discussed.",
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notes = "The Mechanics of Tree-Based GP, Examples of Real-World
Applications of GP, GP Theory, Open Issues",
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size = "31 pages",
- }
Genetic Programming entries for
Leonardo Vanneschi
Riccardo Poli
Citations