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On Synthesis of Metric Interval Temporal Logics

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Automated mining of formal specifications is vital for verifying real-time systems. However, existing passive learning approaches remain restricted to deterministic specifications or limited fragments of Timed Regular Expressions (TRE). To our knowledge, this paper presents the first framework to tackle \emph{precise} passive learning for an expressive timed logic, \emph{Metric Interval Temporal Logic} (MITL) without relying on predefined templates or restricted logic fragments. Our approach formally reduces the timed learning problem into a scalable untimed one. By identifying quantitative ti

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First collected: 2026-09-21T06:11:57.537Z. This is not the publication date.