P. 33-41This 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 discussedS
