Towards Model-driven Fuzzification of Adaptive Systems Specification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10453439" target="_blank" >RIV/00216208:11320/22:10453439 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.5220/0010910800003119" target="_blank" >https://doi.org/10.5220/0010910800003119</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0010910800003119" target="_blank" >10.5220/0010910800003119</a>
Alternative languages
Result language
angličtina
Original language name
Towards Model-driven Fuzzification of Adaptive Systems Specification
Original language description
The position paper outlines a method transforming adaptation rules in a self-adaptive system to a machine learning problem using neural networks. This makes it possible to endow a self-adaptive system with the possibility to learn. At the same time, by controlling the degree to which this transformation is done, one can scale the tradeoff between learning capacity and uncertainty in the self-adaptive system. The paper elaborates this process as a model transformation pipeline. The pipeline starts with a model capturing the strict adaptation rules. Then it is followed by multiple steps in which the strict rules are gradually fuzzified by well-defined transformations. The last model transformation in the pipeline transforms the fuzzified rules to a neural network that can be trained using the traditional stochastic gradient descent method. We briefly showcase this using two examples from the area of collective adaptive systems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GC20-24814J" target="_blank" >GC20-24814J: FluidTrust – Enabling trust by fluid access control to data and physical resources in Industry 4.0 systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 10th International Conference on Model-Driven Engineering and Software Development - MODELSWARD
ISBN
978-989-758-550-0
ISSN
2184-4348
e-ISSN
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Number of pages
8
Pages from-to
336-343
Publisher name
SciTePress
Place of publication
Neuveden
Event location
virtual
Event date
Feb 6, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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