Title :
Using a distance metric on genetic programs to understand genetic operators
Author_Institution :
Artificial Intelligence Lab., MIT, Cambridge, MA
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.637337