Forking Uncertainties: Reliable Prediction and Model Predictive Control With Sequence Models via Conformal Risk Control
Forking Uncertainties: Reliable Prediction and Model Predictive Control With Sequence Models via Conformal Risk Control
In many real-world problems, predictions are leveraged to monitor and control cyber-physical systems, demanding guarantees on the satisfaction of reliability and safety requirements. However, predictions are inherently uncertain, and managing prediction uncertainty presents significant challenges in environments characterized by complex dynamics and forking trajectories. In this work, we assume access …