3 citations · 4 across the 2 of their papers we have counts for
3 papers
Implicit Behavioral Cloning
Pete Florence, Corey Lynch, Andy Zeng +7
We find that across a wide range of robot policy learning scenarios, treating supervised policy learning with an implicit model generally performs better, on average, than commonly…
Forward-Backward Reinforcement Learning
Ashley D. Edwards, Laura Downs, James C. Davidson
Goals for reinforcement learning problems are typically defined through hand-specified rewards. To design such problems, developers of learning algorithms must inherently be aware…
Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
Konstantinos Bousmalis, Alex Irpan, Paul Wohlhart +9
Instrumenting and collecting annotated visual grasping datasets to train modern machine learning algorithms can be extremely time-consuming and expensive. An appealing alternative…