Using Adaptive Sequences for Learning Non-Resettable FSMs


Roland Groz, Nicolas Bremond, Adenilso Simao ;
Proceedings of The 14th International Conference on Grammatical Inference 2018, PMLR 93:30-43, 2019.


This paper proposes a new method to infer non-resettable Mealy machines based on the notions of adaptive homing and characterizing used in FSM testing. This method does not require any knowledge on the system inferred apart from its input set. It progressively extends an output query, and also avoids almost all equivalence queries. It is fast, and scales to machines that have hundreds of states. It outperforms in most respect previous algorithms, and can even compete with algorithms that assume a reset.

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