Abstract
In this work we propose a method to infer context-sensitive languages from positive structural examples produced by linear grammars. Our approach is based on a representation theorem induced by two operations over strings: duplication and reversal. The inference method produces an acceptor device which is an unconventional model of computation based on biomolecules (DNA computing). We prove that a subclass of context-sensitive languages can be inferred by using the representation result in combination with reductions from linear languages to k-testable in the strict sense regular languages.
Work supported by the Spanish Ministerio de Educación y Ciencia under project TIN2007-60769.
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Sempere, J.M. (2008). Learning Context-Sensitive Languages from Linear Structural Information. In: Clark, A., Coste, F., Miclet, L. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2008. Lecture Notes in Computer Science(), vol 5278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88009-7_14
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