284 citations · 1.1k across the 28 of their papers we have counts for
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cs.LG2018★ 254 cited
Learning by Playing - Solving Sparse Reward Tasks from Scratch
Martin Riedmiller, Roland Hafner, Thomas Lampe +6
We propose Scheduled Auxiliary Control (SAC-X), a new learning paradigm in the context of Reinforcement Learning (RL). SAC-X enables learning of complex behaviors - from scratch -…
cs.RO2018★ 67 cited
The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
Markus Giftthaler, Michael Neunert, Markus Stäuble +1
We introduce the Control Toolbox (CT), an open-source C++ library for efficient modeling, control, estimation, trajectory optimization and Model Predictive Control. The CT is appli…