Learning Residual Finite-State Automata Using Observation Tables

Anna Kasprzik
(University of Trier)

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.

In Ian McQuillan and Giovanni Pighizzini: Proceedings Twelfth Annual Workshop on Descriptional Complexity of Formal Systems (DCFS 2010), Saskatoon, Canada, 8-10th August 2010, Electronic Proceedings in Theoretical Computer Science 31, pp. 205–212.
Published: 7th August 2010.

ArXived at: https://dx.doi.org/10.4204/EPTCS.31.23 bibtex PDF

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