31 citations · 31 across the 2 of their papers we have counts for
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cs.LG2019★ 31 cited
End-to-End Robotic Reinforcement Learning without Reward Engineering
Avi Singh, Larry Yang, Kristian Hartikainen +2
The combination of deep neural network models and reinforcement learning algorithms can make it possible to learn policies for robotic behaviors that directly read in raw sensory i…
cs.LG2018
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition
Justin Fu, Avi Singh, Dibya Ghosh +2
The design of a reward function often poses a major practical challenge to real-world applications of reinforcement learning. Approaches such as inverse reinforcement learning atte…
cs.LG2017
GPLAC: Generalizing Vision-Based Robotic Skills using Weakly Labeled Images
Avi Singh, Larry Yang, Sergey Levine
We tackle the problem of learning robotic sensorimotor control policies that can generalize to visually diverse and unseen environments. Achieving broad generalization typically re…