Projects per year
Abstract
The role of crossover and mutation in Genetic Programming (GP) has been the subject of much debate since thee emergence of the field. In this paper, we contribute new empirical evidence to this argument using a rigorous and principled experimental method applied to six problems common in the GP literature. The approach tunes the algorithm parameters to enable a fair and objective comparison of two different GP algorithms, the first using a combination of crossover and reproduction, and secondly using a combination of mutation and reproduction. We find that crossover does not significantly outperform mutation on most of the problems examined. In addition, we demonstrate that the use of a straight forward Design of Experiments methodology is effective at tuning GP algorithm parameters.
Original language | English |
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Title of host publication | GENETIC PROGRAMMING |
Editors | L Vanneschi, S Gustafson, A Moraglio, I DeFalco, M Ebner |
Place of Publication | BERLIN |
Publisher | Springer |
Pages | 220-231 |
Number of pages | 12 |
Volume | 5481 LNCS |
ISBN (Print) | 978-3-642-01180-1 |
Publication status | Published - 2009 |
Event | 12th European Conference on Genetic Programming - Tubingen Duration: 15 Apr 2009 → 17 Apr 2009 |
Conference
Conference | 12th European Conference on Genetic Programming |
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City | Tubingen |
Period | 15/04/09 → 17/04/09 |
Projects
- 1 Finished
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SEBASE: SEBASE: Software Engineering by Automated Search
Clark, J. A. (Principal investigator)
28/06/06 → 4/07/12
Project: Research project (funded) › Research