Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: AI-Assisted Low Information Latency Wireless Networking   The 5G Phase-2 and beyond wireless systems will focus more on vertical
applications such as autonomous driving and industrial Internet-of-things, many
of which are categorized as ultra-Reliable Low-Latency Communications (uRLLC).
In this article, an alternative view on uRLLC is presented, that information
latency, which measures the distortion of information resulted from time lag of
its acquisition process, is more relevant than conventional communication
latency of uRLLC in wireless networked control systems. An AI-assisted
Situationally-aware Multi-Agent Reinforcement learning framework for wireless
neTworks (SMART) is presented to address the information latency optimization
challenge. Case studies of typical applications in Autonomous Driving (AD) are
demonstrated, i.e., dense platooning and intersection management, which show
that SMART can effectively optimize information latency, and more importantly,
information latency-optimized systems outperform conventional uRLLC-oriented
systems significantly in terms of AD performance such as traffic efficiency,
thus pointing out a new research and system design paradigm.

33
The categories of this paper are: plasm-ph
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph