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Integrating ML and uncertainty quantification for real-time decisions in digital twins
US & West ·
A narrative review examines how predictive modeling, machine learning, uncertainty quantification and decision-making are combined in engineering digital twins. It surveys decision architectures and methods addressing their limits across the decision loop, with attention to maintaining them during online operation.
Why it matters
It shows that a digital twin's value comes from the coupling of prediction, uncertainty and decision-making that must be sustained in operation, not from the model alone.
Next-generation wireless networks are increasingly large-scale, heterogeneous, and dynamic, posing significant challenges to network modeling and control. Digital twins offer a promising solution, but existing approaches typically rely on static models and decouple twin construction from network…
Совместное предприятие Selectel и ИТМО «Эмерджентные мультиангентные системы» занимается технологиями для создания и эксплуатации мультиагентных систем: не столько созданием ещё одного отдельного ИИ-ассистента, сколько тем, как сделать эксплуатацию большого количества агентов управляемой, надежной…
