Name
Title | ||
|---|---|---|
Neural clustering analysis of macroevolutionary and genetic algorithms in the evolution of robot controllers |
Abstract | ||
|---|---|---|
In this work, we will use self-organizing feature maps as a method of visualization the sampling of the fitness space considered by the populations of two evolutionary methods, genetic and macroevolutionary algorithms, in a case with a mostly flat fitness landscape and low populations. Macroevolutionary algorithms will allow obtaining better results due to the way in which they handle the exploration-exploitation equilibrium. We test it with different alternatives using the self-organizing maps. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11499305_43 | IWINAC (2) |
Keywords | Field | DocType |
macroevolutionary algorithm,neural clustering analysis,robot controller,genetic algorithm,different alternative,fitness space,flat fitness landscape,self-organizing feature map,exploration-exploitation equilibrium,self-organizing map,better result,evolutionary method,low population,cluster analysis,genetics,fitness landscape | Fitness landscape,Evolutionary algorithm,Computer science,Visualization,Self-organization,Sampling (statistics),Artificial intelligence,Robot,Cluster analysis,Genetic algorithm,Machine learning | Conference |
Volume | ISSN | ISBN |
3562 | 0302-9743 | 3-540-26319-5 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José A. Becerra | 1 | 86 | 16.45 |
| José Santos | 2 | 97 | 14.77 |