An $\mathbf{L^*}$ Algorithm for Deterministic Weighted Regular Languages
Computation and Language
2024-12-20 v2
Abstract
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) 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 directly learns a minimal automaton for the target language.
Keywords
Cite
@article{arxiv.2411.06228,
title = {An $\mathbf{L^*}$ Algorithm for Deterministic Weighted Regular Languages},
author = {Clemente Pasti and Talu Karagöz and Anej Svete and Franz Nowak and Reda Boumasmoud and Ryan Cotterell},
journal= {arXiv preprint arXiv:2411.06228},
year = {2024}
}