Paper ID: 2411.06228

An $\mathbf{L^*}$ Algorithm for Deterministic Weighted Regular Languages

Clemente Pasti, Talu Karagöz, Anej Svete, Franz Nowak, Reda Boumasmoud, Ryan Cotterell

Extracting finite state automata (FSAs) from black-box models offers a powerful approach to gaining interpretable insights into complex model behaviors. To support this pursuit, we present a weighted variant of Angluin's (1987) $\mathbf{L^*}$ algorithm for learning FSAs. We stay faithful to the original algorithm, devising a way to exactly learn deterministic weighted FSAs whose weights support division. Furthermore, we formulate the learning process in a manner that highlights the connection with FSA minimization, showing how $\mathbf{L^*}$ directly learns a minimal automaton for the target language.

Submitted: Nov 9, 2024