Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Joint Estimation of Expertise and Reward Preferences From Human
  Demonstrations   When a robot learns from human examples, most approaches assume that the
human partner provides examples of optimal behavior. However, there are
applications in which the robot learns from non-expert humans. We argue that
the robot should learn not only about the human's objectives, but also about
their expertise level. The robot could then leverage this joint information to
reduce or increase the frequency at which it provides assistance to its human's
partner or be more cautious when learning new skills from novice users.
Similarly, by taking into account the human's expertise, the robot would also
be able of inferring a human's true objectives even when the human's fails to
properly demonstrate these objectives due to a lack of expertise. In this
paper, we propose to jointly infer the expertise level and objective function
of a human given observations of their (possibly) non-optimal demonstrations.
Two inference approaches are proposed. In the first approach, inference is done
over a finite, discrete set of possible objective functions and expertise
levels. In the second approach, the robot optimizes over the space of all
possible hypotheses and finds the objective function and expertise level that
best explain the observed human behavior. We demonstrate our proposed
approaches both in simulation and with real user data.

10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th