Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-agent Deep Reinforcement Learning with Extremely Noisy
  Observations   Multi-agent reinforcement learning systems aim to provide interacting agents
with the ability to collaboratively learn and adapt to the behaviour of other
agents. In many real-world applications, the agents can only acquire a partial
view of the world. Here we consider a setting whereby most agents' observations
are also extremely noisy, hence only weakly correlated to the true state of the
environment. Under these circumstances, learning an optimal policy becomes
particularly challenging, even in the unrealistic case that an agent's policy
can be made conditional upon all other agents' observations. To overcome these
difficulties, we propose a multi-agent deep deterministic policy gradient
algorithm enhanced by a communication medium (MADDPG-M), which implements a
two-level, concurrent learning mechanism. An agent's policy depends on its own
private observations as well as those explicitly shared by others through a
communication medium. At any given point in time, an agent must decide whether
its private observations are sufficiently informative to be shared with others.
However, our environments provide no explicit feedback informing an agent
whether a communication action is beneficial, rather the communication policies
must also be learned through experience concurrently to the main policies. Our
experimental results demonstrate that the algorithm performs well in six highly
non-stationary environments of progressively higher complexity, and offers
substantial performance gains compared to the baselines.

37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol