Recently, we have been witnessing a rapid increase in the use of machine learning
techniques in self-adaptive systems. Machine learning has been used for a variety of …

Context: Self-adaptive systems have been studied in software engineering over the past few
decades attempting to address challenges within the field. There is a continuous significant …

The research initiative “self-improving system integration”(SISSY) was established with the
goal to master the ever-changing demands of system organisation in the presence of …

In this article, we make the case for the new class of Self-aware Cyber-physical Systems. By
bringing together the two established fields of cyber-physical systems and self-aware …

The self-improving system integration (SISSY) initiative-sometimes also called self-
integration-started over six years ago. Recently, we have seen contributions approaching …

There have been a number of approaches to employ neural networks in self-adaptive
systems; in many cases, generic neural networks and deep learning are utilized for this …

Integrated networked systems sense a common environment, learn to navigate the
environment and share their experiences. Sharing experiences simplifies learning, reducing …

Reinforcement Learning (RL) can generally be distinguished into two main classes: model-
based and model-free. While model-based approaches use some kind of model of the …

As artificial intelligence (AI) has already seen numerous successful applications, the
upcoming challenge lies in how to realize artificial general intelligence (AGI). Self-learning …

There have been a number of approaches to employing neural networks (NNs) in self-
adaptive systems; in many cases, generic NNs/deep learning are utilized for this purpose …