5 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 5 cited
Deep Black-Box Reinforcement Learning with Movement Primitives
Fabian Otto, Onur Celik, Hongyi Zhou +3
\Episode-based reinforcement learning (ERL) algorithms treat reinforcement learning (RL) as a black-box optimization problem where we learn to select a parameter vector of a contro…
cs.LG2022★ 3 cited
Specializing Versatile Skill Libraries using Local Mixture of Experts
Onur Celik, Dongzhuoran Zhou, Ge Li +2
A long-cherished vision in robotics is to equip robots with skills that match the versatility and precision of humans. For example, when playing table tennis, a robot should be cap…
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…