: This study presents an evolution strategy used to infer fuzzy finite-state automata from examples of a fuzzy language. We describe the fitness function of an generated automata with respect to a set of examples of a fuzzy language, the representation of the transition of the automata as well as the output of the states in the evolution strategy and the simple mutation operators that work on these representations. Results are reported on the inference of a fuzzy language. Key words: Evolution strategy, fuzzy finite state automata, mutation, fitness, generalization