5 citations · 24 across the 16 of their papers we have counts for
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Learning Temporal Logic Properties: an Overview of Two Recent Methods
Jean-Raphaël Gaglione, Rajarshi Roy, Nasim Baharisangari +3
Learning linear temporal logic (LTL) formulas from examples labeled as positive or negative has found applications in inferring descriptions of system behavior. We summarize two me…
Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise
Igor Khmelnitsky, Serge Haddad, Lina Ye +5
Angluin's L* algorithm learns the minimal (complete) deterministic finite automaton (DFA) of a regular language using membership and equivalence queries. Its probabilistic approxim…
Learning Interpretable Temporal Properties from Positive Examples Only
Rajarshi Roy, Jean-Raphaël Gaglione, Nasim Baharisangari +3
We consider the problem of explaining the temporal behavior of black-box systems using human-interpretable models. To this end, based on recent research trends, we rely on the fund…
Specification sketching for Linear Temporal Logic
Simon Lutz, Daniel Neider, Rajarshi Roy
Virtually all verification and synthesis techniques assume that the formal specifications are readily available, functionally correct, and fully match the engineer's understanding…
Robust Computation Tree Logic
Satya Prakash Nayak, Daniel Neider, Rajarshi Roy +1
It is widely accepted that every system should be robust in that ``small'' violations of environment assumptions should lead to ``small'' violations of system guarantees, but it is…