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Found 4 papers, 2 papers with code
Online ML Self-adaptation in Face of Traps
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.
Ensemble-based modeling abstractions for modern self-optimizing systems
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.
Towards fuzzification of adaptation rules in self-adaptive architectures
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.
Forming Ensembles at Runtime: A Machine Learning Approach
To tackle this problem, in this paper we propose to recast the ensemble formation problem as a classification problem and use machine learning to efficiently form ensembles at scale.
