TY  - GEN
AU  - Vinuesa,Hernán
AU  - Lanzarini,Laura Cristina
TI  - Neural Networks Elitist Evolution
KW  - ROBÓTICA
N1  - Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática-UNLP (Colección BIPA / Biblioteca.); International Conference on Information Technology Interfaces (29th : 2007 : Duvrovnik)
N2  - This paper presents an elitist evolving strategy, which allows obtaining a controller, based on a neural network capable of commanding an autonomous robot. In order to reduce the detrimental crossover effect, we propose to use a strategy to create several children for each parent pair, selecting properly the way of making the replacement. The results obtained   that, though the number ofchildren is high, the quantity of fitness tests carried out is actually lower than that of aconventional evolving algorithm. In this way, we propose an alternative that reduces thecomputational cost of the process, reaching at a suitable response for the problem resolution
ER  -