This paper presents a genetic algorithm based approach to the automatic discovery of finitestate a u t o m a t a (FSAs) from positive data. FSAs are commonly used in computational phonology, but - given the limited learnability of FSAs from arbitrary language subsets - are usually constructed manually. The approach presented here offers a practical automatic method that helps reduce the cost of manual FSA construction.