Policies often fail due to distribution shift – changes in the state and...
Robots have been increasingly better at doing tasks for humans by learni...
To act in the world, robots rely on a representation of salient task asp...
When robots learn reward functions using high capacity models that take ...
One of the most successful paradigms for reward learning uses human feed...
As robots are increasingly deployed in real-world scenarios, a key quest...
Our goal is to enable robots to perform functional tasks in emotive ways...
Reward learning enables robots to learn adaptable behaviors from human i...
Robots need to be able to learn concepts from their users in order to ad...
Shared autonomy enables robots to infer user intent and assist in
accomp...
As environments involving both robots and humans become increasingly com...
In collaborative human-robot scenarios, when a person is not satisfied w...
Human input has enabled autonomous systems to improve their capabilities...
Robots need models of human behavior for both inferring human goals and
...
Learning robot objective functions from human input has become increasin...