Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards fuzzification of adaptation rules in self-adaptive architectures   In this paper, we focus on exploiting neural networks for the analysis and
planning stage in self-adaptive architectures. The studied motivating cases in
the paper involve existing (legacy) self-adaptive architectures and their
adaptation logic, which has been specified by logical rules. We further assume
that there is a need to endow these systems with the ability to learn based on
examples of inputs and expected outputs. One simple option to address such a
need is to replace the reasoning based on logical rules with a neural network.
However, this step brings several problems that often create at least a
temporary regress. The reason is the logical rules typically represent a large
and tested body of domain knowledge, which may be lost if the logical rules are
replaced by a neural network. Further, the black-box nature of generic neural
networks obfuscates how the systems work inside and consequently introduces
more uncertainty. In this paper, we present a method that makes it possible to
endow an existing self-adaptive architectures with the ability to learn using
neural networks, while preserving domain knowledge existing in the logical
rules. We introduce a continuum between the existing rule-based system and a
system based on a generic neural network. We show how to navigate in this
continuum and create a neural network architecture that naturally embeds the
original logical rules and how to gradually scale the learning potential of the
network, thus controlling the uncertainty inherent to all soft computing
models. We showcase and evaluate the approach on representative excerpts from
two larger real-life use cases.

17
The categories of this paper are: q-fin
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
18
The categories of this paper are: econ
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph