ModellingEnhanced Imitation Learning of Model Predictive Control through Importance WeightingarXiv — Systems and Control (eess.SY) · 2dModellingLimited knowledge exchange across biological subfields in agent-based modellingarXiv — Physics and Society (physics.soc-ph) · 2dDigital twinReasoner-checked ontology crosswalks for a national digital twinarXiv API — полнотекстовый поиск "digital twin" · 3dDigital twinDigital twin speeds up reinforcement learning for lab robotsarXiv API — полнотекстовый поиск "digital twin" · 3dDigital twinDataset for deciding between evidence gathering and action in control-system incidentsarXiv — Computational Engineering, Finance, and Science (cs.CE) · 3dDigital twinSparse stochastic twins can outperform exact digital twinsarXiv — Computational Engineering, Finance, and Science (cs.CE) · 3dModellingPluralism of rival models in network models of sciencearXiv — Multiagent Systems (cs.MA) · 3dForecastingEstimation and MPC for balancing a wheel-legged robot under unknown disturbancesarXiv — Systems and Control (eess.SY) · 3dDigital twinConsolidating dispersed DSO data into a digital twin of the distribution gridarXiv API — полнотекстовый поиск "digital twin" · 4dDigital twinIntegrating ML and uncertainty quantification for real-time decisions in digital twinsarXiv API — полнотекстовый поиск "digital twin" · 4dDigital twinBiases in end-to-end digital twins built from chained modelsarXiv API — полнотекстовый поиск "digital twin" · 4dDigital twinDistributed Bandits for Freshness-Aware Data in MEC-Enabled Digital TwinsarXiv API — полнотекстовый поиск "digital twin" · 4d
Digital Twins for Students: Toward Precision Education
US & West ·
The article proposes a 'Precision Education' paradigm that uses digital twins of students, predictive models, and learning analytics to shift from reactive responses to academic failure toward prevention and support. The approach draws on an analogy with healthcare, where predictive models helped shift the focus to prevention.
Why it matters
This extends digital twin application to human-centric systems and shows how predictive modeling can manage complex social processes.
From Precision Medicine to Precision Education: A Vision for AI-Powered Student Digital Twins, Preventive Student Success, and Career-Aligned Academic Pathways
The work defines a formal criterion for valid mappings between digital twin ontologies: coherence and conservativity of the merged ontology. It is applied to the Information Exchange Standard and thirteen ontologies anchored on BOT, Brick and SAREF4BLDG, through matching, human review, certification and reasoning with HermiT.
TwinBridge builds digital twins from 3D Gaussian splatting and physics simulation to supply policy initialization and dense visual rewards for real-world online learning of a laboratory robot. Simulator task events and geometric progress yield rewards for pretraining, distilled into a visual reward model and combined with execution history during human-in-the-loop refinement.
The authors present TE-GvA, a counterfactual decision dataset for fault-driven incident response on the revised Tennessee Eastman process: 9,908 decision points from 1,990 simulated incidents, each with 4–35 candidate actions labelled via branched rollouts. With labels computed under the true hidden cause, gathering evidence is the best choice in only 1.1–1.3% of decisions.
