- Heike Clemens (for administrative matters)
- A Collective Adaptive Approach to Decentralised k-Coverage in Multi-Robot Systems : article - Pianini, Danilo; Pettinari, Federico; Casadei, Roberto; Esterle, Lukas - New York : ACM, 2022. - 38 pp. - (ACM transactions on autonomous and adaptive systems ; 2022).
- On Learning in Collective Self-adaptive Systems : State of Practice and a 3D Framework : article in 2019 IEEE / ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) - D'Angelo, Mirko; Gerasimou, Simos; Ghahremani, Sona; Grohmann, Johannes; Pournaras, Evangelos; Tomforde, Sven; Nunes, Ingrid - Los Alamitos : IEEE, 2019. - pp. 13-24.
- On Learning in Collective Self-adaptive Systems : State of Practice and a 3D Framework : article to be presented at the 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2019) - D'Angelo, Mirko; Gerasimou, Simos; Ghahremani, Sona; Grohmann, Johannes; Pournaras, Evangelos; Tomforde, Sven; Nunes, Ingrid - York : University, 2019. - 14 pp..
- Planning as Optimization : Dynamically Discovering Optimal Configurations for Runtime Situations - Fredericks, Erick M.; Gerostathopoulos, Ilias; Krupitzer, Christian; Vogel, Thomas - Cornell University : arXiv.org, 2019. - 10 pp..
- Software Engineering for Intelligent and Autonomous Systems : Report from the GI Dagstuhl Seminar 18343 - Gerasimou, Simos; Vogel, Thomas; Diaconescu, Ada - Cornell University : arXiv.org, 2019. - 14 pp..
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. To tackle this challenge, researchers and practitioners investigate how to engineer intelligent and autonomous software systems capable of dynamically adapting themselves without any or with limited human involvement. Through using closed-loop control, typically realized with software, these systems can autonomously identify abnormal situations, analyse alternative adaptation options, and finally, self-adapt to a suitable new configuration.
Over the past years, several research communities have devoted significant efforts to devise methodologies, algorithms and frameworks for engineering autonomous computing systems. Some noteworthy examples include the SEAMS, ICAC/ICCAC, SASO, Self-Aware Computing and AAMAS communities. Irrespective of the incarnation and particular focus of each community, the main objective remains the same, that is, to make computing systems more intelligent and autonomous.
Despite the mutual interests, these communities typically participate in disjoint research forums such as workshops, conferences and journals. Hence, they rarely have the opportunity to meet in a common venue. The SEfIAS GI-Dagstuhl seminar aims to bridge the gap between these communities and make an initial step towards strengthening interaction and collaboration between these communities.
The main goal of the SEfIAS GI-Dagstuhl seminar is to bring together early-career researchers from the SEAMS, ICAC/ICCAC, SASO, Self-Aware Computing and AAMAS communities working in the area of software engineering for intelligent and autonomous systems.
The seminar has the following specific objectives:
- Enable researchers to present their research and learn about the state-of-the-art approaches and methodologies from adjacent fields
- Provide a forum for demonstrating the research activities conducted by the individual communities with the purpose of identifying commonalities and differences among these communities
- Strengthen interaction among researchers by exchanging ideas, discussing research challenges and establishing collaborations towards joint research projects
- Envision the future of engineering intelligent and autonomous systems