Abstract
This work addresses the problem of the inference of non deterministic automata (NFA) from given positive and negative samples. We propose here to consider this problem as a particular case of the inference of unambiguous finite state classifier. We are then able to present an efficient incompatibility NFA detection framework for state merging inference process.
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Coste, F., Fredouille, D. (2000). Efficient Ambiguity Detection in C-NFA. In: Oliveira, A.L. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2000. Lecture Notes in Computer Science(), vol 1891. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45257-7_3
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DOI: https://doi.org/10.1007/978-3-540-45257-7_3
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