Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Decentralization of Multiagent Policies by Learning What to Communicate   Effective communication is required for teams of robots to solve
sophisticated collaborative tasks. In practice it is typical for both the
encoding and semantics of communication to be manually defined by an expert;
this is true regardless of whether the behaviors themselves are bespoke,
optimization based, or learned. We present an agent architecture and training
methodology using neural networks to learn task-oriented communication
semantics based on the example of a communication-unaware expert policy. A
perimeter defense game illustrates the system's ability to handle dynamically
changing numbers of agents and its graceful degradation in performance as
communication constraints are tightened or the expert's observability
assumptions are broken.

30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
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The categories of this paper are: econ
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat