21 citations · 39 across the 4 of their papers we have counts for
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cs.RO2021
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale
Dmitry Kalashnikov, Jacob Varley, Yevgen Chebotar +5
General-purpose robotic systems must master a large repertoire of diverse skills to be useful in a range of daily tasks. While reinforcement learning provides a powerful framework…
cs.RO2021★ 13 cited
The Distracting Control Suite -- A Challenging Benchmark for Reinforcement Learning from Pixels
Austin Stone, Oscar Ramirez, Kurt Konolige +1
Robots have to face challenging perceptual settings, including changes in viewpoint, lighting, and background. Current simulated reinforcement learning (RL) benchmarks such as DM C…