Abstract
Recently an algorithm to identify in the limit with polynomial time and data Left Deterministic Linear Languages (Left DLL) and, consequently Right DLL, was proposed. In this paper we show that the class of the Left-Right DLL formed by the union of both classes is also identifiable. To do that, we introduce the notion of n-negative characteristic sample, that is a sample that forces an inference algorithm to output an hypothesis of size bigger than n when strings from a non identifiable language are provided.
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de la Higuera, C., Oncina, J.: Learning deterministic linear languages. In: Kivinen, J., Sloan, R.H. (eds.) COLT 2002. LNCS (LNAI), vol. 2375, pp. 185–200. Springer, Heidelberg (2002)
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© 2004 Springer-Verlag Berlin Heidelberg
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Calera-Rubio, J., Oncina, J. (2004). Identifying Left-Right Deterministic Linear Languages. In: Paliouras, G., Sakakibara, Y. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2004. Lecture Notes in Computer Science(), vol 3264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30195-0_29
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DOI: https://doi.org/10.1007/978-3-540-30195-0_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23410-4
Online ISBN: 978-3-540-30195-0
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