Efficient Ambiguity Detection in C-NFA, a Step Towards the Inference on Non Deterministic Automata

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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