Sort by
Refine Your Search
-
. They involve high-stakes decisions with important trade-offs and uncertainties. They are also challenged by the data sampling process which gives rise to distribution shifts when comparing past and future data
-
and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
-
responsibility is to conduct high-quality research on hybrid artificial intelligence. You will: Combine deep learning to capture long-term patterns and uncertainties with stochastic model predictive control
Searches related to uncertainty
Enter an email to receive alerts for uncertainty positions