no code implementations • 11 Sep 2023 • Michal Töpfer, František Plášil, Tomáš Bureš, Petr Hnětynka, Martin Kruliš, Danny Weyns
Recently, we experimented with applying online ML for self-adaptation of a smart farming scenario and we had faced several unexpected difficulties -- traps -- that, to our knowledge, are not discussed enough in the community.
1 code implementation • 11 Sep 2023 • Michal Töpfer, Milad Abdullah, Tomáš Bureš, Petr Hnětynka, Martin Kruliš
In this paper, we extend our ensemble-based component model DEECo with the capability to use machine-learning and optimization heuristics in establishing and reconfiguration of autonomic component ensembles.
1 code implementation • 3 Jan 2022 • Adam Šmelko, Soňa Molnárová, Miroslav Kratochvíl, Abhishek Koladiya, Jan Musil, Martin Kruliš, Jiří Vondrášek
Dimensionality reduction methods have found vast application as visualization tools in diverse areas of science.
no code implementations • 17 Dec 2021 • Tomáš Bureš, Petr Hnětynka, Martin Kruliš, Danylo Khalyeyev, Sebastian Hahner, Stephan Seifermann, Maximilian Walter, Robert Heinrich
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.