Robotics and Bioinspired Systems
Model uncertainty refers to the lack of confidence in a model's ability to accurately represent the real-world system it is intended to simulate or predict. This uncertainty can arise from various sources such as incomplete knowledge of the system, simplifications made during model development, or inaccuracies in the data used for model calibration. Understanding model uncertainty is crucial for improving decision-making and reliability in fields like robotics and soft sensor development.
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