Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Visual Sensor Network Reconfiguration with Deep Reinforcement Learning   We present an approach for reconfiguration of dynamic visual sensor networks
with deep reinforcement learning (RL). Our RL agent uses a modified
asynchronous advantage actor-critic framework and the recently proposed
Relational Network module at the foundation of its network architecture. To
address the issue of sample inefficiency in current approaches to model-free
reinforcement learning, we train our system in an abstract simulation
environment that represents inputs from a dynamic scene. Our system is
validated using inputs from a real-world scenario and preexisting object
detection and tracking algorithms.

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The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
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The categories of this paper are: econ
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th