Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Getting to Know One Another: Calibrating Intent, Capabilities and Trust
  for Human-Robot Collaboration   Common experience suggests that agents who know each other well are better
able to work together. In this work, we address the problem of calibrating
intention and capabilities in human-robot collaboration. In particular, we
focus on scenarios where the robot is attempting to assist a human who is
unable to directly communicate her intent. Moreover, both agents may have
differing capabilities that are unknown to one another. We adopt a
decision-theoretic approach and propose the TICC-POMDP for modeling this
setting, with an associated online solver. Experiments show our approach leads
to better team performance both in simulation and in a real-world study with
human subjects.

11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc