Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine Learning in Event-Triggered Control: Recent Advances and Open
  Issues   Network Control Systems (NCSs) have attracted much interest over the past
decade as part of a move towards more decentralised control applications and
the rise of cyberphysical system applications. Many practical NCSs face the
challenges of limited communication bandwidth resources, reliability and lack
of knowledge of network dynamics, particularly when wireless networks are
involved. Machine learning (ML) combined with event-triggered control (ETC) has
the potential to ease some of these challenges. For example, ML can be used to
overcome the problem of a lack of network models by learning system behaviour
or adapt to dynamically changing models by continually learning model dynamics.
ETC can help to conserve bandwidth resources by communicating only when needed
or when resources are available. Here, we present a review of the literature on
work that combines ML and ETC. The literature on supervised, semi-supervised,
unsupervised and reinforcement learning based approaches such as deep
reinforcement learning and statistical learning in combination with ETC is
explored. Furthermore, the difference between the application of these learning
algorithms on model-based and model-free systems are discussed. Following the
analysis of the literature, we highlight open research questions and challenges
related to ML-based ETC and propose approaches to possible solutions to these
challenges.

31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int