On sufficient conditions to identify in the limit classes of grammars from polynomial time and data

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Abstract

Linearity and determinism seem to be two essential conditions for polynomial learning of grammars to be possible. We propose a general condition valid for certain subclasses of the linear grammars given which these classes can be polynomially identified in the limit from given data. This enables us to give new proofs of the identification of well known classes of grammars, and to propose a new (and larger) class of linear grammars for which polynomial identification is thus possible.

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De La Higuera, C., & Oncina, J. (2002). On sufficient conditions to identify in the limit classes of grammars from polynomial time and data. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2484, pp. 134–148). Springer Verlag. https://doi.org/10.1007/3-540-45790-9_11

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