Learning Commutative Regular Languages

Authors:
Antonio Cano Gómez;Gloria I. Álvarez
Affiliations:
Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, (Spain);Departamento de Ciencias e Ingeniería de la Computación, Pontificia Universidad Javeriana Cali, Cali, Colombia No. 118-250
Venue:
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Year:
2008

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Abstract

In this article we study the inference of commutative regular languages. We first show that commutative regular languages are not inferable from positive samples, and then we study the possible improvement of inference from positive and negative samples. We propose a polynomial algorithm to infer commutative regular languages from positive and negative samples, and we show, from experimental results, that far from being a theoretical algorithm, it produces very high recognition rates in comparison with classical inference algorithms.