DocumentCode
2409822
Title
Using a distance metric on genetic programs to understand genetic operators
Author
O´Reilly, U.-M.
Author_Institution
Artificial Intelligence Lab., MIT, Cambridge, MA
Volume
5
fYear
1997
fDate
12-15 Oct 1997
Firstpage
4092
Abstract
I describe a distance metric called “edit” distance which quantifies the syntactic difference between two genetic programs. In the context of one specific problem, the 6 bit multiplexor, I use the metric to analyze the amount of new material introduced by different crossover operators, the difference among the best individuals of a population and the difference among the best individuals and the rest of the population. The relationships between these data and run performance are imprecise but they are sufficiently interesting to encourage further investigation into the use of edit distance
Keywords
genetic algorithms; search problems; software metrics; software performance evaluation; trees (mathematics); best individuals; crossover operators; distance metric; edit distance; genetic operators; genetic programs; multiplexor; population; run performance; search; syntactic difference; trees; Artificial intelligence; Genetic programming; Information analysis; Performance analysis; Sampling methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location
Orlando, FL
ISSN
1062-922X
Print_ISBN
0-7803-4053-1
Type
conf
DOI
10.1109/ICSMC.1997.637337
Filename
637337
Link To Document