Search Results for author: Nasim Baharisangari

Found 5 papers, 1 papers with code

Learning Temporal Logic Properties: an Overview of Two Recent Methods

no code implementations2 Dec 2022 Jean-Raphaël Gaglione, Rajarshi Roy, Nasim Baharisangari, Daniel Neider, Zhe Xu, Ufuk Topcu

Learning linear temporal logic (LTL) formulas from examples labeled as positive or negative has found applications in inferring descriptions of system behavior.

Distributed Differentially Private Control Synthesis for Multi-Agent Systems with Metric Temporal Logic Specifications

no code implementations4 Oct 2022 Nasim Baharisangari, Zhe Xu

In this paper, we propose a distributed differentially private receding horizon control (RHC) approach for multi-agent systems (MAS) with metric temporal logic (MTL) specifications.

Learning Interpretable Temporal Properties from Positive Examples Only

no code implementations6 Sep 2022 Rajarshi Roy, Jean-Raphaël Gaglione, Nasim Baharisangari, Daniel Neider, Zhe Xu, Ufuk Topcu

To learn meaningful models from positive examples only, we design algorithms that rely on conciseness and language minimality of models as regularizers.

Weighted Graph-Based Signal Temporal Logic Inference Using Neural Networks

no code implementations16 Sep 2021 Nasim Baharisangari, Kazuma Hirota, Ruixuan Yan, Agung Julius, Zhe Xu

It is important that the obtained knowledge is human-interpretable and amenable to formal analysis.


Uncertainty-Aware Signal Temporal Logic Inference

1 code implementation24 May 2021 Nasim Baharisangari, Jean-Raphaël Gaglione, Daniel Neider, Ufuk Topcu, Zhe Xu

In this paper, we first investigate the uncertainties associated with trajectories of a system and represent such uncertainties in the form of interval trajectories.

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