This paper for the first time attempts to bridge the knowledge between
c...
Deep neural networks often fail catastrophically by relying on spurious
...
There is an increasing interest in learning reward functions that model ...
Robot swarms often exhibit emergent behaviors that are fascinating to
ob...
Preference-based reinforcement learning (PbRL) can enable robots to lear...
Learning a reward function from human preferences is challenging as it
t...
When robots learn reward functions using high capacity models that take ...
Recent work in sim2real has successfully enabled robots to act in physic...
In this paper we examine the problem of determining demonstration suffic...
When inferring reward functions from human behavior (be it demonstration...
Simulation-to-reality transfer has emerged as a popular and highly succe...
Our goal is to enable robots to perform functional tasks in emotive ways...
Previous work defined Exploratory Grasping, where a robot iteratively gr...
Effective robot learning often requires online human feedback and
interv...
We study how an offline dataset of prior (possibly random) experience ca...
In industrial part kitting, 3D objects are inserted into cavities for
tr...
The difficulty in specifying rewards for many real-world problems has le...
Many robotics domains use some form of nonconvex model predictive contro...
Shared autonomy enables robots to infer user intent and assist in
accomp...
Corrective interventions while a robot is learning to automate a task pr...
As environments involving both robots and humans become increasingly com...
As humans interact with autonomous agents to perform increasingly
compli...
There has been significant recent work on data-driven algorithms for lea...
One of the main challenges in imitation learning is determining what act...
Bayesian reward learning from demonstrations enables rigorous safety and...
Bayesian inverse reinforcement learning (IRL) methods are ideal for safe...
The performance of imitation learning is typically upper-bounded by the
...
A critical flaw of existing inverse reinforcement learning (IRL) methods...
Active learning from demonstration allows a robot to query a human for
s...
Inverse reinforcement learning (IRL) infers a reward function from
demon...
In the field of reinforcement learning there has been recent progress to...