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A comparison of GE and TAGE in dynamic environments
Author(s)
Date Issued
2011-07-12
Date Available
2012-02-21T15:23:48Z
Abstract
The lack of study of genetic programming in dynamic environments is recognised as a known issue in the field of genetic programming. This study compares the performance of two forms of genetic programming, grammatical evolution and a variation of grammatical evolution which uses tree-adjunct grammars, on a series of dynamic problems. Mean best fitness plots for the two representations are analysed and compared.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2011 ACM
Subject – LCSH
Genetic programming (Computer science)
Evolutionary computation
Web versions
Language
English
Status of Item
Peer reviewed
Journal
GECCO '11 : Proceedings of the 13th annual conference on Genetic and evolutionary computation
Conference Details
Paper presented at the ACM Genetic and Evolutionary Computation Conference, GECCO 2011, 12-16 July, Dublin, Ireland
ISBN
978-1-4503-0557-0
This item is made available under a Creative Commons License
File(s)
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Name
fp692-murphy-draft.pdf
Size
1.15 MB
Format
Adobe PDF
Checksum (MD5)
98e9584a33472611bd286247da60b82b
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