2024-03-28T09:01:11Zhttp://buleria.unileon.es/oai/requestoai:buleria.unileon.es:10612/19072023-05-30T11:13:25Zcom_10612_17col_10612_21
Learning Fuzzy Reactive Behaviors in Autonomous Robots
Matellán Olivera, Vicente
Molina, José Manuel
Sánz, Javier
Fernández Llamas, Camino
Arquitectura y Tecnologia de Computadores
Informática
This paper is concerned with the learning of basic behaviors in autonomous robots. In this way, we present a method for the adaptation of basic reactive behaviors implemented as fuzzy
controllers applying a genetic algorithm to the evolution of the fuzzy rule system. In this sense, we
show our experiments in the evolution of control rules based on symbolic concepts represented as
linguistic labels. The rules will be formulated in a fuzzy way and in order to test the rules obtained
in each generation of the genetic algorithm a real robot has been used. The individual with the best
performance is chosen to generate a new population: the elite strategy. All the new individuals were
tested in the same real environment. In conclusion, the individuals of the last generation offer a set
of rules that provides better performance than the ones designed by a non-expert designer
2012-10-11
2012-10-11
2012-10-11
info:eu-repo/semantics/conferenceObject
IV European Workshop on Learning Robots, 1995, Karlsruhe (Alemania)
http://hdl.handle.net/10612/1907
info:eu-repo/semantics/openAccess