2024-03-29T11:53:52Zhttp://buleria.unileon.es/oai/requestoai:buleria.unileon.es:10612/19882020-12-10T08:57:41Zcom_10612_17col_10612_18
Genetic learning of fuzzy reactive controllers
Matellán Olivera, Vicente
Fernández Llamas, Camino
Arquitectura y Tecnologia de Computadores
Escuela de Ingenierias Industrial e Informatica
Informática
Robots autónomos
Fuzzy
Algoritmos genéticos
Búsqueda
P. 33-41
This paper concerns the learning of basic behaviors in an autonomous robot. It presents a method to adapt basic reactive
behaviors using a genetic algorithm. Behaviors are implemented as fuzzy controllers and the genetic algorithm is used to
evolve their rules. These rules will be formulated in a fuzzy way using prefixed linguistic labels. In order to test the rules
obtained in each generation of the genetic evolution process, a real robot has been used. Numerical results from the evolution
rate of the different experiments, as well as an example of the fuzzy rules obtained, are presented and discussed
SI
1998-10-26
2012-11-09T10:58:35Z
2012-11-09T10:58:35Z
2012-11-09
info:eu-repo/semantics/article
Robotics and Autonomous Systems, 1998, vol. 25, n. 1-2
http://hdl.handle.net/10612/1988
eng
info:eu-repo/semantics/openAccess
Elsevier
https://buleria.unileon.es/bitstream/10612/1988/4/Camino.pdf.jpg
Hispana
TEXT
http://rightsstatements.org/vocab/CNE/1.0/
BULERIA. Repositorio Institucional de la Universidad de León
http://hdl.handle.net/10612/1988