9 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.RO2019★ 1 cited
Learning Reward Functions by Integrating Human Demonstrations and Preferences
Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk +1
Our goal is to accurately and efficiently learn reward functions for autonomous robots. Current approaches to this problem include inverse reinforcement learning (IRL), which uses…
cs.RO2019★ 9 cited
Unsupervised Visuomotor Control through Distributional Planning Networks
Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh +1
While reinforcement learning (RL) has the potential to enable robots to autonomously acquire a wide range of skills, in practice, RL usually requires manual, per-task engineering o…