Large language models such as OpenAI's GPT and Google's Bard offer new opportunities
for supporting software engineering processes. Large language model assisted software …

Quantum computing is an emerging paradigm that enables to solve a variety of problems
more efficiently than it is possible on classical computers. As the first quantum computers are …

State-of-the-art multi-agent reinforcement learning has achieved remarkable success in
recent years. The success has been mainly based on the assumption that all teammates …

Abstract The development of Machine Learning (ML) models is more than just a special
case of software development (SD): ML models acquire properties and fulfill requirements …

An adaptive system is able to adapt at runtime to dynamically changing environments and to
new requirements. Adaptive systems can be single adaptive entities or collective ones that …

We discuss the synergetic connection between quantum computing and artificial
intelligence. After surveying current approaches to quantum artificial intelligence and …

An adaptive system is able to adapt at runtime to dynamically changing environments and to
new requirements. Adaptive systems can be single adaptive entities or collective ones that …

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 …

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 …

Autonomous systems need to be able dynamically adapt to changing requirements and
environmental conditions without redeployment and without interruption of the systems …