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eess.SY2021
Model-Based Reinforcement Learning via Stochastic Hybrid Models
Hany Abdulsamad, Jan Peters
Optimal control of general nonlinear systems is a central challenge in automation. Enabled by powerful function approximators, data-driven approaches to control have recently succe…
eess.SY2021
Distributionally Robust Trajectory Optimization Under Uncertain Dynamics via Relative Entropy Trust-Regions
Hany Abdulsamad, Tim Dorau, Boris Belousov +2
Trajectory optimization and model predictive control are essential techniques underpinning advanced robotic applications, ranging from autonomous driving to full-body humanoid cont…
eess.SY2019
Chance-Constrained Trajectory Optimization for Non-linear Systems with Unknown Stochastic Dynamics
Onur Celik, Hany Abdulsamad, Jan Peters
Iterative trajectory optimization techniques for non-linear dynamical systems are among the most powerful and sample-efficient methods of model-based reinforcement learning and app…