IdMAT and LIndA enable learning any regular language consistent with an incomplete inductive teacher by reducing uncertainties to incremental SAT solving for tasks like language separation and invariant synthesis.
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cs.FL 2years
2026 2verdicts
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An L#-inspired active learning algorithm learns minimal separating DFAs for disjoint languages when one exists and outperforms prior methods on random and industrial benchmarks.
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Automata Learning with an Incomplete but Inductive Teacher (Technical Report)
IdMAT and LIndA enable learning any regular language consistent with an incomplete inductive teacher by reducing uncertainties to incremental SAT solving for tasks like language separation and invariant synthesis.
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An $L^{\#}$ Based Algorithm for Active Learning of Minimal Separating Automata
An L#-inspired active learning algorithm learns minimal separating DFAs for disjoint languages when one exists and outperforms prior methods on random and industrial benchmarks.