@inproceedings{a249e23c4f88442093c4a3ef20705249,
title = "Learning a deterministic finite automaton with a recurrent neural network",
abstract = "We consider the problem of learning a finite automaton with recurrent neural networks from positive evidence. We train an Elman recurrent neural network with a set of sentences in a language and extract a finite automaton by clustering the states of the trained network. We observe that the generalizations beyond the training set, in the language recognized by the extracted automaton, are due to the training regime: the network performs a “loose” minimization of the prefix DFA of the training set, the automaton that has a state for each prefix of the sentences in the set.",
author = "Laura Firoiu and Tim Oates and Cohen, {Paul R.}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1998.; 4th International Colloquium on Grammatical Inference, ICGI 1998 ; Conference date: 12-07-1998 Through 14-07-1998",
year = "1998",
doi = "10.1007/bfb0054067",
language = "English (US)",
isbn = "3540647767",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "90--101",
editor = "Vasant Honavar and Giora Slutzki",
booktitle = "Grammatical Inference - 4th International Colloquium, ICGI 1998, Proceedings",
}