Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-lingual agents through multi-headed neural networks   This paper considers cooperative Multi-Agent Reinforcement Learning, focusing
on emergent communication in settings where multiple pairs of independent
learners interact at varying frequencies. In this context, multiple distinct
and incompatible languages can emerge. When an agent encounters a speaker of an
alternative language, there is a requirement for a period of adaptation before
they can efficiently converse. This adaptation results in the emergence of a
new language and the forgetting of the previous language. In principle, this is
an example of the Catastrophic Forgetting problem which can be mitigated by
enabling the agents to learn and maintain multiple languages. We take
inspiration from the Continual Learning literature and equip our agents with
multi-headed neural networks which enable our agents to be multi-lingual. Our
method is empirically validated within a referential MNIST based communication
game and is shown to be able to maintain multiple languages where existing
approaches cannot.

3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
21
The categories of this paper are: adap-org
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The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas