8 citations · 16 across the 9 of their papers we have counts for
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cs.LG2019★ 6 cited
Sub-Goal Trees -- a Framework for Goal-Directed Trajectory Prediction and Optimization
Tom Jurgenson, Edward Groshev, Aviv Tamar
Many AI problems, in robotics and other domains, are goal-directed, essentially seeking a trajectory leading to some goal state. In such problems, the way we choose to represent a…
cs.RO2019
Harnessing Reinforcement Learning for Neural Motion Planning
Tom Jurgenson, Aviv Tamar
Motion planning is an essential component in most of today's robotic applications. In this work, we consider the learning setting, where a set of solved motion planning problems is…