Abstract
TreeEvolver, a genetic programming algorithm, is used to make continuous mathematical functions that give rise to 3D landscapes. These are then empirically tested for hardness by a simple evolutionary algorithm, after which TreeEvolver mutates the functions in an effort to increase the hardness of the corresponding landscapes. Results are wildly diverse, but show that traditional continuous benchmark functions such as Branin, Easom and Martin-Gaddy might not be hard at all, and much harder objective landscapes exist.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 26th International Conference on Enterprise Information Systems |
| Subtitle of host publication | Volume 1: ICEIS |
| Editors | Joaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi |
| Publisher | Science and Technology Publications, Lda |
| Pages | 567-578 |
| Number of pages | 12 |
| Volume | 1 |
| ISBN (Electronic) | 9789897586927 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 26th International Conference on Enterprise Information Systems, ICEIS 2024 - Angers, France Duration: 28 Apr 2024 → 30 Apr 2024 |
Publication series
| Name | International Conference on Enterprise Information Systems, ICEIS - Proceedings |
|---|---|
| ISSN (Electronic) | 2184-4992 |
Conference
| Conference | 26th International Conference on Enterprise Information Systems, ICEIS 2024 |
|---|---|
| Country/Territory | France |
| City | Angers |
| Period | 28/04/24 → 30/04/24 |
Bibliographical note
Publisher Copyright:Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.
Keywords
- Evolutionary Algorithms
- Fitness Landscapes
- Genetic Programming