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Grammar-based genetic programming : a survey

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Author(s)
McKay, Bob (Bob I.) 
Nguyen, Xuan Hoai 
Whigham, P. A. (Peter A.) 
Shan, Yin 
O'Neill, Michael 
Uri
http://hdl.handle.net/10197/2592
Date Issued
01 May 2010
Date Available
24T16:59:11Z November 2010
Abstract
Grammar formalisms are one of the key representation structures in Computer Science. So it is not surprising that they have also become important as a method for formalizing constraints in Genetic Programming (GP). Practical grammar-based GP systems first appeared in the mid 1990s, and have subsequently become an important strand in GP research and applications. We trace their subsequent rise, surveying the various grammar-based formalisms that have been used in GP and discussing the contributions they have made to the progress of GP. We illustrate these contributions with a range of applications of grammar-based GP, showing how grammar formalisms contributed to the solutions of these problems. We briefly discuss the likely future development of grammar-based GP systems, and conclude with a brief summary of the field.
Sponsorship
Science Foundation Ireland
Type of Material
Journal Article
Publisher
Springer
Journal
Genetic Programming and Evolvable Machines
Volume
11
Issue
3-4
Start Page
365
End Page
396
Copyright (Published Version)
Springer Science+Business Media, LLC 2010
Keywords
  • Genetic programming

  • Evolutionary computat...

  • Grammar

  • Context free

  • Regular

  • Tree adjoining

Subject – LCSH
Genetic programming (Computer science)
Evolutionary computation
DOI
10.1007/s10710-010-9109-y
Web versions
The final publication is available at www.springerlink.com/content/2g72q01860204683/
http://dx.doi.org/10.1007/s10710-010-9109-y
Language
English
Status of Item
Peer reviewed
ISSN
1389-2576 (Print)
1573-7632 (Online)
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
Owning collection
Computer Science Research Collection
Scopus© citations
247
Acquisition Date
Jan 26, 2023
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Views
1686
Acquisition Date
Jan 27, 2023
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Downloads
4257
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4
Acquisition Date
Jan 27, 2023
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