Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural SLAM: Learning to Explore with External Memory   We present an approach for agents to learn representations of a global map
from sensor data, to aid their exploration in new environments. To achieve
this, we embed procedures mimicking that of traditional Simultaneous
Localization and Mapping (SLAM) into the soft attention based addressing of
external memory architectures, in which the external memory acts as an internal
representation of the environment. This structure encourages the evolution of
SLAM-like behaviors inside a completely differentiable deep neural network. We
show that this approach can help reinforcement learning agents to successfully
explore new environments where long-term memory is essential. We validate our
approach in both challenging grid-world environments and preliminary Gazebo
experiments. A video of our experiments can be found at: https://goo.gl/G2Vu5y.

18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio