Loading...
Please wait, while we are loading the content...
Similar Documents
Visual Analytics of EA Data
| Content Provider | Hyper Articles en Ligne (HAL) |
|---|---|
| Author | Lutton, Evelyne Fekete, Jean-Daniel |
| Abstract | An experimental analysis of evolutionary algorithms usually generates a huge amount of multidimensional data, including numeric and symbolic data. It is difficult to efficiently navigate in such a set of data, for instance to be able to tune the parameters or evaluate the efficiency of some operators. Usual features of existing EA visualisation systems consist in visualising time- or generation-dependent curves (fitness, diversity, or other statistics). When dealing with genomic information, the task becomes even more difficult, as a convenient visualisation strongly depends on the considered fitness landscape. In this latter case the raw data are usually sets of suc- cessive populations of points of a complex multidimensional space. The purpose of this paper is to evaluate the potential interest of a recent visual analytics tool for navigating in complex sets of EA data, and to sketch future developements of this tool, in order to better adapt it to the needs of EA experimental analysis. |
| Related Links | https://inria.hal.science/hal-00642300/file/LuttonGECCO2011.pdf |
| Conference Proceedings | Genetic and Evolutionary Computation Conference |
| Language | English |
| Publisher | HAL CCSD |
| Publisher Date | 2011-07-12 |
| Access Restriction | Open |
| Subject Keyword | Visualisation of Evolutionary Algorithms Artificial Evolution |
| Content Type | Text |
| Resource Type | Conference Proceedings |
| Subject | Computer Science |
