arXiv Computation and Language By Anna Di Placido (UniCA, Laboratoire I3S - COMRED, KAIROS), Nicolas Ferry (UniCA, Laboratoire I3S - COMRED, KAIROS), Julien Deantoni (UniCA, Laboratoire I3S - COMRED, KAIROS)

Towards Illusions Awareness in Cyber-Physical System's Design

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arXiv AI
Aug 13

A Conceptual Framework for Refining Influence Knowledge from Simulation Evidence in Cyber-Physical Systems

arXiv:2608. 11221v1 Announce Type: new Abstract: Cyber-physical systems (CPS) are typically developed by multiple stakeholders who produce artefacts tailored to their specific domains of expertise.

By Barbara da Silva Oliveira (UniCA, Laboratoire I3S - COMRED, KAIROS), Julien Deantoni (UniCA, Laboratoire I3S - COMRED, KAIROS), Nicolas Ferry (Laboratoire I3S - COMRED, KAIROS, UniCA)
arXiv Machine Learning
Sep 11

Estimating Inconsistency Response Surfaces under Uncertainty in Cyber-Physical System Development

The paper presents a method to estimate inconsistency response surfaces in Cyber‑Physical Systems (CPS) under uncertainty. By reformulating inconsistency as an intervention‑response modeling problem, the authors use Saltelli sampling and multi‑fidelity Monte Carlo estimation to generate datasets, then train a surrogate model that predicts inconsistency from propagated uncertainty geometry. Experiments on 48 scenarios across 10 CPS domains show that the surrogate matches Monte Carlo estimates while dramatically reducing evaluation time, enabling extensive sensitivity analysis and a gradient‑based consistency recourse method to identify minimal interventions that restore consistency.

By Johannes M\"akelburg, Tim Schwabe, Maribel Acosta
arXiv AI
3d ago

An Empirical Study of Architectural Shift from Traditional to AI-Enabled Simulink Controllers

The paper reports an empirical study comparing traditional and AI‑enabled Simulink controllers, using a taxonomy of ten structural categories and nine functional roles. Analyzing 62 real‑world models and surveying 13 practitioners, it finds that subsystem organization dominates all controller architectures, AI models rely heavily on discrete dynamics and user‑defined abstraction, and constraint enforcement blocks largely disappear in AI‑enabled designs. These findings highlight architectural tensions and gaps between AI literature and practical implementation.

By Hadiza Umar Yusuf, Khouloud Gaaloul