Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cooperative Queuing Policies for Effective Human-Multi-Robot Interaction   We consider multi-robot applications, where a team of robots can ask for the
intervention of a human operator to handle difficult situations. As the number
of requests grows, team members will have to wait for the operator attention,
hence the operator becomes a bottleneck for the system. Our aim in this context
is to make the robots learn cooperative strategies to decrease the time spent
waiting for the operator. In particular, we consider a queuing model where
robots decide whether or not to join the queue and use multi-robot learning to
estimate the best cooperative policy. In more detail, we formalize the problem
as Decentralized Markov Decision Process and provide a suitable state
representation, so to apply an independent learners approach. We evaluate the
proposed method in a robotic water monitoring simulation and empirically show
that our approach can significantly improve the team performance, while being
computationally tractable.

16
The categories of this paper are: stat
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc