no code implementations • 22 Jul 2019 • Andreas Metzger, Clément Quinton, Zoltán Ádám Mann, Luciano Baresi, Klaus Pohl
Existing online learning techniques randomly explore the possible adaptation actions, but this can lead to slow convergence of the learning process.
no code implementations • 24 Feb 2022 • Tsung-Hao Huang, Andreas Metzger, Klaus Pohl
We thus see growing interest in explainable predictive business process monitoring, which aims to increase the interpretability of prediction models.
no code implementations • 12 Oct 2022 • Felix Feit, Andreas Metzger, Klaus Pohl
Online reinforcement learning, i. e., employing reinforcement learning (RL) at runtime, is an emerging approach to realizing self-adaptive systems in the presence of design time uncertainty.
no code implementations • 9 Jul 2023 • Andreas Metzger, Jan Laufer, Felix Feit, Klaus Pohl
However, Online RL requires the definition of an effective and correct reward function, which quantifies the feedback to the RL algorithm and thereby guides learning.
no code implementations • 12 Jul 2023 • Andreas Metzger, Tristan Kley, Aristide Rothweiler, Klaus Pohl
This means that acting on less accurate predictions may lead to unnecessary adaptations or missed adaptations.
1 code implementation • 25 Sep 2023 • Andreas Metzger, Jone Bartel, Jan Laufer
Compared to earlier work on natural-language explanations using classical software-based dialogue systems, using an AI chatbot eliminates the need for eliciting and defining potential questions and answers up-front.
no code implementations • 26 Oct 2023 • Xhulja Shahini, Domenic Bubel, Andreas Metzger
These stochastic elements, also known as nondeterminism-introducing (NI) factors, lead to variance in the training process and as a result, lead to variance in prediction accuracy and training time.
1 code implementation • 2 Jul 2015 • Pooyan Jamshidi, Amir Sharifloo, Claus Pahl, Andreas Metzger, Giovani Estrada
The benefit is that for designing cloud controllers, we do not have to rely solely on precise design-time knowledge, which may be difficult to acquire.