Learning Residual Finite-State Automata Using Observation Tables
Formal Languages and Automata Theory
2010-08-11 v1
Abstract
We define a two-step learner for RFSAs based on an observation table by using an algorithm for minimal DFAs to build a table for the reversal of the language in question and showing that we can derive the minimal RFSA from it after some simple modifications. We compare the algorithm to two other table-based ones of which one (by Bollig et al. 2009) infers a RFSA directly, and the other is another two-step learner proposed by the author. We focus on the criterion of query complexity.
Keywords
Cite
@article{arxiv.1008.1663,
title = {Learning Residual Finite-State Automata Using Observation Tables},
author = {Anna Kasprzik},
journal= {arXiv preprint arXiv:1008.1663},
year = {2010}
}
Comments
In Proceedings DCFS 2010, arXiv:1008.1270