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Inverse Optimal Control as an Errors-in-Variables Problem
Inverse optimal control (IOC) is about estimating an unknown objective of interest given its optimal control sequence.
Active Learning-based Model Predictive Coverage Control
In addition, we derive a control framework that avoids the hierarchical structure by integrating the reference optimization in the MPC formulation.
On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics
Many finance, physics, and engineering phenomena are modeled by continuous-time dynamical systems driven by highly irregular (stochastic) inputs.
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