Software Engineering for Intelligent and Autonomous Systems: Report from the GI Dagstuhl Seminar 18343

TL;DR

This report summarizes research on adaptive software systems that can dynamically respond to unpredictable environments and failures, emphasizing the role of closed-loop control in autonomous system self-adaptation.

Contribution

It provides an overview of recent advancements in self-adaptive software systems within autonomous and intelligent systems, highlighting collaborative efforts and research directions.

Findings

Enhanced understanding of dynamic adaptation mechanisms.

Identification of key challenges in autonomous system safety.

Promotion of interdisciplinary collaboration in self-adaptive systems.

Abstract

Software systems are increasingly used in application domains characterised by uncertain environments, evolving requirements and unexpected failures; sudden system malfunctioning raises serious issues of security, safety, loss of comfort or revenue. During operation, these systems will likely need to deal with several unpredictable situations including variations in system performance, sudden changes in system workload and component failures. These situations can cause deviation from the desired system behaviour and require dynamic adaptation of the system behaviour, parameters or architecture. Through using closed-loop control, typically realized with software, intelligent and autonomous software systems can dynamically adapt themselves, without any or with limited human involvement, by identifying abnormal situations, analysing alternative adaptation options, and finally, self-adapting to a suitable new configuration. This report summarises the research carried out during SEfIAS GI Dagstuhl seminar which provided a forum for strengthening interaction and collaboration for early-career researchers and practitioners from the research communities of SEAMS, ICAC/ICCAC, SASO, Self-Aware Computing and AAMAS.