5 papers · 1 filter
Learning Dynamics from Infrequent Output Measurements for Uncertainty-Aware Optimal Control
Robert Lefringhausen, Theodor Springer, Sandra Hirche
Reliable optimal control is challenging when the dynamics of a nonlinear system are unknown and only infrequent, noisy output measurements are available. This work addresses this s…
Barrier Certificates for Unknown Systems with Latent States and Polynomial Dynamics using Bayesian Inference
Robert Lefringhausen, Sami Leon Noel Aziz Hanna, Elias August +1
Certifying safety in dynamical systems is crucial, but barrier certificates - widely used to verify that system trajectories remain within a safe region - typically require explici…
Online Bayesian Learning of Agent Behavior in Differential Games
Francesco Bianchin, Robert Lefringhausen, Sandra Hirche
This work introduces an online Bayesian game-theoretic method for behavior identification in multi-agent dynamical systems. By casting Hamilton-Jacobi-Bellman optimality conditions…
A Set-Theoretic Robust Control Approach for Linear Quadratic Games with Unknown Counterparts
Francesco Bianchin, Robert Lefringhausen, Elisa Gaetan +2
Ensuring robust decision-making in multi-agent systems is challenging when agents have distinct, possibly conflicting objectives and lack full knowledge of each other's strategies.…
Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States
Robert Lefringhausen, Supitsana Srithasan, Armin Lederer +1
As control engineering methods are applied to increasingly complex systems, data-driven approaches for system identification appear as a promising alternative to physics-based mode…