6 citations · 14 across the 8 of their papers we have counts for
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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.RO2022★ 2 cited
ProDMPs: A Unified Perspective on Dynamic and Probabilistic Movement Primitives
Ge Li, Zeqi Jin, Michael Volpp +3
Movement Primitives (MPs) are a well-known concept to represent and generate modular trajectories. MPs can be broadly categorized into two types: (a) dynamics-based approaches that…