Tag
This paper presents the first application of calibration models for offline hyperparameter selection in a real-world industrial setting, using a municipal water treatment plant, and shows they can generate realistic rollouts and recover hyperparameter sensitivity trends.
This paper explores using a compact Small Language Model (Qwen2.5-1.5B) retrained with GRPO and combined with a validator-guided correction loop for autonomous industrial control. The framework achieves high alignment accuracy and low latency, demonstrating practical viability for edge deployment.
This paper introduces a predictive formulation for deep reinforcement learning that augments the state space with future reference horizons to enable anticipatory control for trajectory tracking. Simulation results show significant error reduction, though zero-shot transfer to physical hardware reveals a sim-to-real gap.
Het rapport onderzoekt de digitale afhankelijkheid van de energie-intensieve industrie in Nederland van niet-Europese clouddiensten en concludeert dat de meest cruciale systemen nog grotendeels autonoom zijn, maar de ondersteunende laag en logistiek sterk afhankelijk zijn van meerdere buitenlandse clouds, wat risico's oplevert bij verstoringen.