Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CoLight: Learning Network-level Cooperation for Traffic Signal Control   Cooperation among the traffic signals enables vehicles to move through
intersections more quickly. Conventional transportation approaches implement
cooperation by pre-calculating the offsets between two intersections. Such
pre-calculated offsets are not suitable for dynamic traffic environments. To
enable cooperation of traffic signals, in this paper, we propose a model,
CoLight, which uses graph attentional networks to facilitate communication.
Specifically, for a target intersection in a network, CoLight can not only
incorporate the temporal and spatial influences of neighboring intersections to
the target intersection, but also build up index-free modeling of neighboring
intersections. To the best of our knowledge, we are the first to use graph
attentional networks in the setting of reinforcement learning for traffic
signal control and to conduct experiments on the large-scale road network with
hundreds of traffic signals. In experiments, we demonstrate that by learning
the communication, the proposed model can achieve superior performance against
the state-of-the-art methods.

25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph