%0 Conference Paper %1 oreilly:1997:dnGPugo2 %A O'Reilly, Una-May %B IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation %C Orlando, Florida, USA %D 1997 %K algorithms, best crossover difference, distance distance, edit genetic individuals, metric, multiplexor, operators, performance, population, programming, programs, run search, syntactic trees %P 4092--4097 %T Using a Distance Metric on Genetic Programs to Understand Genetic Operators %U http://ieeexplore.ieee.org/iel4/4942/13793/00637337.pdf %V 5 %X 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. %@ 0-7803-4053-1

@inproceedings{oreilly:1997:dnGPugo2, 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.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Orlando, Florida, USA}, author = {O'Reilly, Una-May}, biburl = {https://www.bibsonomy.org/bibtex/2cde91a67de4006894ef231103f864a0e/brazovayeye}, booktitle = {IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation}, interhash = {122cb2be00ad79c6546c396f5f100417}, intrahash = {cde91a67de4006894ef231103f864a0e}, isbn = {0-7803-4053-1}, keywords = {algorithms, best crossover difference, distance distance, edit genetic individuals, metric, multiplexor, operators, performance, population, programming, programs, run search, syntactic trees}, month = {12-15 October}, notes = {{"}fair crossover{"} (no 90/10 bias), {"}Height fair crossover{"} and normal subtree crossover}, pages = {4092--4097}, timestamp = {2008-06-19T17:49:05.000+0200}, title = {Using a Distance Metric on Genetic Programs to Understand Genetic Operators}, url = {http://ieeexplore.ieee.org/iel4/4942/13793/00637337.pdf}, volume = 5, year = 1997 }