arXiv AI By Barbara da Silva Oliveira (UniCA, Laboratoire I3S - COMRED, KAIROS), Julien Deantoni (UniCA, Laboratoire I3S - COMRED, KAIROS), Nicolas Ferry (Laboratoire I3S - COMRED, KAIROS, UniCA)

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

Read the original on arXiv AI →

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.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Computation and Language
Sep 16

Towards Illusions Awareness in Cyber-Physical System's Design

arXiv:2609.17260v1 Announce Type: new Abstract: Cyber-Physical Systems (CPS) operate through a continuous sense-compute-act loop within an open context environment, making it impossible to anticipate...

By Anna Di Placido (UniCA, Laboratoire I3S - COMRED, KAIROS), Nicolas Ferry (UniCA, Laboratoire I3S - COMRED, KAIROS), Julien Deantoni (UniCA, Laboratoire I3S - COMRED, KAIROS)
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
OpenAI Blog
Oct 19, 2017

Generalizing from simulation

Our latest robotics techniques allow robot controllers, trained entirely in simulation and deployed on physical robots, to react to unplanned changes in the environment as they solve simple tasks. That is, we’ve used these techniques to build closed-loop systems rather than open-loop ones as before.