16 citations · 60 across the 34 of their papers we have counts for
9 papers · 1 filter
Learning Temporal Properties is NP-hard
Benjamin Bordais, Daniel Neider, Rajarshi Roy
We investigate the complexity of LTL learning, which consists in deciding given a finite set of positive ultimately periodic words, a finite set of negative ultimately periodic wor…
Synthesizing Efficiently Monitorable Formulas in Metric Temporal Logic
Ritam Raha, Rajarshi Roy, Nathanael Fijalkow +2
In runtime verification, manually formalizing a specification for monitoring system executions is a tedious and error-prone process. To address this issue, we consider the problem…
Inferring Properties in Computation Tree Logic
Rajarshi Roy, Daniel Neider
We consider the problem of automatically inferring specifications in the branching-time logic, Computation Tree Logic (CTL), from a given system. Designing functional and usable sp…
Defending Our Privacy With Backdoors
Dominik Hintersdorf, Lukas Struppek, Daniel Neider +1
The proliferation of large AI models trained on uncurated, often sensitive web-scraped data has raised significant privacy concerns. One of the concerns is that adversaries can ext…
Robust Alternating-Time Temporal Logic
Aniello Murano, Daniel Neider, Martin Zimmermann
In multi-agent system design, a crucial aspect is to ensure robustness, meaning that for a coalition of agents A, small violations of adversarial assumptions only lead to small vio…
Reinforcement Learning with Temporal-Logic-Based Causal Diagrams
Yash Paliwal, Rajarshi Roy, Jean-Raphaël Gaglione +5
We study a class of reinforcement learning (RL) tasks where the objective of the agent is to accomplish temporally extended goals. In this setting, a common approach is to represen…