Learning Deterministic Finite Automata from Smallest Counterexamples
Abstract. We show that deterministic finite automata (DFAs) with n states and input alphabet Sigma can efficiently be learned from less than
Lehrstuhl Mathematik & InformatikAbstract. We show that deterministic finite automata (DFAs) with n states and input alphabet Sigma can efficiently be learned from less than