68 citations · 139 across the 18 of their papers we have counts for
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cs.RO2019★ 9 cited
Reinforcement Learning without Ground-Truth State
Xingyu Lin, Harjatin Singh Baweja, David Held
To perform robot manipulation tasks, a low-dimensional state of the environment typically needs to be estimated. However, designing a state estimator can sometimes be difficult, es…
cs.RO2019★ 1 cited
Adaptive Variance for Changing Sparse-Reward Environments
Xingyu Lin, Pengsheng Guo, Carlos Florensa +1
Robots that are trained to perform a task in a fixed environment often fail when facing unexpected changes to the environment due to a lack of exploration. We propose a principled…