%0 Conference Paper %1 meysenburg:1999:RGQGP %A Meysenburg, Mark M. %A Foster, James A. %B Proceedings of the Genetic and Evolutionary Computation Conference %C Orlando, Florida, USA %D 1999 %E Banzhaf, Wolfgang %E Daida, Jason %E Eiben, Agoston E. %E Garzon, Max H. %E Honavar, Vasant %E Jakiela, Mark %E Smith, Robert E. %I Morgan Kaufmann %K algorithms, and evolvable genetic hardware programming %P 1121--1126 %T Random Generator Quality and GP Performance %U http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-416.ps %V 2 %X In previous studies, the authors found that pseudo-random number generator (PRNG) quality had little effect on the performance of a simple genetic algorithm (GA). This paper extends our work to the area of genetic programming (GP). We examine the effect of PRNG quality on the performance of GP techniques. We detail a set of PRNGs which generate random numbers through various techniques, and a method for evaluating the quality of these PRNGs. We explain the application of detailed statistical analysis to the results of many individual GP runs, over a set of four GP test problems. We found no evidence to support the notion that higher quality PRNGs caused improved GP performance. %@ 1-55860-611-4

@inproceedings{meysenburg:1999:RGQGP, abstract = {In previous studies, the authors found that pseudo-random number generator (PRNG) quality had little effect on the performance of a simple genetic algorithm (GA). This paper extends our work to the area of genetic programming (GP). We examine the effect of PRNG quality on the performance of GP techniques. We detail a set of PRNGs which generate random numbers through various techniques, and a method for evaluating the quality of these PRNGs. We explain the application of detailed statistical analysis to the results of many individual GP runs, over a set of four GP test problems. We found no evidence to support the notion that higher quality PRNGs caused improved GP performance.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Orlando, Florida, USA}, author = {Meysenburg, Mark M. and Foster, James A.}, biburl = {https://www.bibsonomy.org/bibtex/24fff907e638f63b80e8034209340711d/brazovayeye}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference}, editor = {Banzhaf, Wolfgang and Daida, Jason and Eiben, Agoston E. and Garzon, Max H. and Honavar, Vasant and Jakiela, Mark and Smith, Robert E.}, interhash = {c3a4b3f8c4c8ed299f9b67efafbcd6aa}, intrahash = {4fff907e638f63b80e8034209340711d}, isbn = {1-55860-611-4}, keywords = {algorithms, and evolvable genetic hardware programming}, month = {13-17 July}, notes = {GECCO-99 A joint meeting of the eighth international conference on genetic algorithms (ICGA-99) and the fourth annual genetic programming conference (GP-99)}, pages = {1121--1126}, publisher = {Morgan Kaufmann}, publisher_address = {San Francisco, CA 94104, USA}, timestamp = {2008-06-19T17:47:02.000+0200}, title = {Random Generator Quality and {GP} Performance}, url = {http://www.cs.bham.ac.uk/~wbl/biblio/gecco1999/GP-416.ps}, volume = 2, year = 1999 }