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20162026
most citedDeepMind Control Suite

521 citations · 1.2k across the 41 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.RO2021★ 16 cited

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes

Alex X. Lee, Coline Devin, Yuxiang Zhou +18

We study the problem of robotic stacking with objects of complex geometry. We propose a challenging and diverse set of such objects that was carefully designed to require strategie…

cs.RO2021★ 1 cited

Evaluating model-based planning and planner amortization for continuous control

Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim +8

There is a widespread intuition that model-based control methods should be able to surpass the data efficiency of model-free approaches. In this paper we attempt to evaluate this i…

cs.LG2021★ 3 cited

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning: Case Studies in Offline RL and Finetuning

Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani +11

Many advances that have improved the robustness and efficiency of deep reinforcement learning (RL) algorithms can, in one way or another, be understood as introducing additional ob…

cs.AI2021★ 12 cited

From Motor Control to Team Play in Simulated Humanoid Football

Siqi Liu, Guy Lever, Zhe Wang +19

Intelligent behaviour in the physical world exhibits structure at multiple spatial and temporal scales. Although movements are ultimately executed at the level of instantaneous mus…

cs.LG2021

Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning

William F. Whitney, Michael Bloesch, Jost Tobias Springenberg +3

Despite the close connection between exploration and sample efficiency, most state of the art reinforcement learning algorithms include no considerations for exploration beyond max…