14 citations · 25 across the 9 of their papers we have counts for
11 papers
Robust Imitation of a Few Demonstrations with a Backwards Model
Jung Yeon Park, Lawson L. S. Wong
Behavior cloning of expert demonstrations can speed up learning optimal policies in a more sample-efficient way over reinforcement learning. However, the policy cannot extrapolate…
Binding Actions to Objects in World Models
Ondrej Biza, Robert Platt, Jan-Willem van de Meent +2
We study the problem of binding actions to objects in object-factored world models using action-attention mechanisms. We propose two attention mechanisms for binding actions to obj…
Factored World Models for Zero-Shot Generalization in Robotic Manipulation
Ondrej Biza, Thomas Kipf, David Klee +3
World models for environments with many objects face a combinatorial explosion of states: as the number of objects increases, the number of possible arrangements grows exponentiall…
Natural Language for Human-Robot Collaboration: Problems Beyond Language Grounding
Seth Pate, Wei Xu, Ziyi Yang +3
To enable robots to instruct humans in collaborations, we identify several aspects of language processing that are not commonly studied in this context. These include location, pla…
Bad-Policy Density: A Measure of Reinforcement Learning Hardness
David Abel, Cameron Allen, Dilip Arumugam +3
Reinforcement learning is hard in general. Yet, in many specific environments, learning is easy. What makes learning easy in one environment, but difficult in another? We address t…
Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps
Chengguang Xu, Christopher Amato, Lawson L. S. Wong
In robot navigation, generalizing quickly to unseen environments is essential. Hierarchical methods inspired by human navigation have been proposed, typically consisting of a high-…