Efficient Induction of Finite State Automata
Abstract
This paper introduces a new algorithm for the induction of complex finite state automata from samples of behaviour. The algorithm is based on information theoretic principles. The algorithm reduces the search space by many orders of magnitude over what was previously thought possible. We compare the algorithm with some existing induction techniques for finite state automata and show that the algorithm is much superior in both run time and quality of inductions.
Cite
Text
Collins and Oliver. "Efficient Induction of Finite State Automata." Conference on Uncertainty in Artificial Intelligence, 1997.Markdown
[Collins and Oliver. "Efficient Induction of Finite State Automata." Conference on Uncertainty in Artificial Intelligence, 1997.](https://mlanthology.org/uai/1997/collins1997uai-efficient/)BibTeX
@inproceedings{collins1997uai-efficient,
title = {{Efficient Induction of Finite State Automata}},
author = {Collins, Matthew S. and Oliver, Jonathan J.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1997},
pages = {99-107},
url = {https://mlanthology.org/uai/1997/collins1997uai-efficient/}
}