18 citations · 36 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 18 cited
Generalized Hindsight for Reinforcement Learning
Alexander C. Li, Lerrel Pinto, Pieter Abbeel
One of the key reasons for the high sample complexity in reinforcement learning (RL) is the inability to transfer knowledge from one task to another. In standard multi-task RL sett…
cs.RO2019★ 18 cited
Learning to Manipulate Deformable Objects without Demonstrations
Yilin Wu, Wilson Yan, Thanard Kurutach +2
In this paper we tackle the problem of deformable object manipulation through model-free visual reinforcement learning (RL). In order to circumvent the sample inefficiency of RL, w…