日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

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シミュレーションarXiv:2608.11221v1

サイバーフィジカルシステムにおけるシミュレーション証拠からの影響知識を洗練するための概念的枠組み

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

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本論文は、サイバーフィジカルシステムのシミュレーション結果をより深く理解するために、「影響」という新しい概念を用いた概念的枠組みを提案し、モバイルロボットのケーススタディで実証している。

著者: Barbara da Silva Oliveira, Julien Deantoni, Nicolas Ferry

分類: cs.AI

原文アブストラクト

Cyber-physical systems (CPS) are typically developed by multiple stakeholders who produce artefacts tailored to their specific domains of expertise. The behaviour of these systems emerges from the interaction between those artefacts and their operational environment. Simulation and co-simulation have become essential approaches for analysing CPS behaviour and, through simulation campaigns, developers can explore system responses under changing conditions, including interactions with the environment. However, the lack of details and understanding of some environmentmediated interactions (typically the ones beyond direct sensing and actuation), which remain unmodelled due to their complexity, a lack of time, or a lack of domain experience, hinders the proper comprehension and exploitation of simulation results. To address these limitations, we propose a conceptual framework leveraging the novel concept of Influences to support the iterative and incremental refinement of simulation campaigns and deepen the understanding of the system behaviour. We demonstrate the proposed approach through a case study involving a mobile robot implemented using Simulink/Gazebo co-simulation.

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