Modern distributed systems and Internet-of-Things applications are governed by fast living
and changing requirements. Moreover, they have to struggle with huge amounts of data that …

Proactive adaptation improves the system performance of Autonomic Computing systems as
it recognizes adaptation concerns in advance and adapts or prepares adaptation …

❖ Interpretability by design• Knowledge represented by IF-THEN rules• Allows for explicit
injection of expert knowledge❖ Complexity reduction by design❖ Online adaptivity to …

In this paper, we show how an evolutionary rule-based machine learning technique can be
applied to tackle the task of self-configuration of smart camera networks. More precisely, the …

In many areas of decision-making, forecasting is an essential pillar. Consequently, many
different forecasting methods have been proposed. From our experience, recently presented …

These days, we are living in a digitalized world. Both our professional and private lives are
pervaded by various IT services, which are typically operated using distributed computing …

Self-adaptive systems are increasingly endowed with Artificial Intelligence technology in
order to enhance system autonomy. Most prominently, algorithms from the research field of …

This paper aims to propose a novel Organic Computing concept to dealing with the overall
issue of automated design of processing pipelines. It is outlined how several methods …

Deep Learning methods have become increasingly popular for time-series forecasting in
recent years. One common way of improving time-series forecasts is to use ensembles. By …

The research field of forecasting deals with the prediction of future observations by
examining the history. Thus, forecasting is an important part of the decision-making process …