A genetic algorithm for regular inference
Faculty of Computing, Health and Science
School of Computer and Information Science
We show how a genetic algorithm can be used for the inference of a regular language from a set of positive (and optionally also negative) examples. The genetic algorithm attempts to find the simplest description of the example data in terms of a finite state automaton model.