Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adversarial Resilience Learning - Towards Systemic Vulnerability
  Analysis for Large and Complex Systems   This paper introduces Adversarial Resilience Learning (ARL), a concept to
model, train, and analyze artificial neural networks as representations of
competitive agents in highly complex systems. In our examples, the agents
normally take the roles of attackers or defenders that aim at worsening or
improving-or keeping, respectively-defined performance indicators of the
system. Our concept provides adaptive, repeatable, actor-based testing with a
chance of detecting previously unknown attack vectors. We provide the
constitutive nomenclature of ARL and, based on it, the description of
experimental setups and results of a preliminary implementation of ARL in
simulated power systems.

26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
2
The categories of this paper are: math
24
The categories of this paper are: dg-ga
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph