AI RESEARCH

Monitoring Data-aware Temporal Properties (Extended Version)

arXiv CS.AI

ArXi:2605.14666v1 Announce Type: new Dynamic systems in AI are often complex and heterogeneous, so that an internal specification is not accessible and verification techniques such as model checking are not applicable. Monitoring is in such cases an attractive alternative, as it evaluates desirable properties along traces generated by an unknown dynamic system. In this work, we consider anticipatory monitoring of linear-time properties enriched with an arbitrary SMT theory over finite traces (LTLfMT.