Paper Info
Title
A comparison of GE and TAGE in dynamic environments
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.
Year
DOI
Venue
2011
10.1145/2001576.2001763
GECCO
Keywords
Field
DocType
best fitness plot,known issue,genetic programming,dynamic problem,dynamic environment,grammatical evolution,tree-adjunct grammar,representation
Rule-based machine translation,Dynamical optimization,Computer science,Genetic programming,Artificial intelligence,Genetic representation,Grammatical evolution,Dynamic problem,Machine learning
Conference
Citations 
PageRank 
References 
2
0.41
9
Authors
3
Name
Order
Citations
PageRank
Eoin Murphy1405.01
Michael O'Neill287669.58
Anthony Brabazon391898.60