Intelligent Systems Workshop – 7th edition in the

Series on Autonomously Learning and Optimising Systems (SAOS)

co-located with 32nd GI/ITG ARCS 2019 in Copenhagen, Denmark from May 20 to May 23, 2019

Download Call for Papers

 

Aims and Scope of SAOS

Complexity in Information and Communication Technology (ICT) is still increasing, driven by the growing number of devices with vast amounts of computational resources. As a result, the administration of present and future systems becomes an impossibility for central human operators. To tackle this development, modern systems are increasingly equipped with techniques and algorithms that allow them to act `intelligently’. Such Intelligent Systems (IS) strongly leverage the recent advances in Artificial Intelligence (AI) in general and of Machine Learning (ML) in particular. With this workshop, we provide a forum for presenting and discussing novel concepts, techniques and algorithms for IS as well as for related aspects such as quantification approaches to peak into the black box often involved.

An IS is characterized by its autonomous learning behaviour, which includes mechanisms to relieve the human from non-trivial tasks such as hyperparameter optimisation, algorithm selection and continual monitoring in the pursuit of recognising changes, anomalies, etc. The degree of system autonomy shall be increased as far as possible by still complying with the necessary safety boundaries apparent in nearly any real-world application. As a result, the vision of initiatives such as Organic Computing and Autonomic Computing manifests itself: traditional design-time decisions are moved to run time and, thus, the systems themselves take over control.

In this workshop, we solicit research and position papers that encompass the application of novel and established ML techniques. Thereby, we explicitly emphasize the aspect of interpretability and explainability of the involved algorithms to provide a basis for system transparency already at the core of its mechanisms. Besides this self-explanation property of the targeted systems, another ingredient to reach a specific level of intelligence is self-awareness and the resulting, ongoing pursuit for self-optimisation. This particular tension between system learning, optimisation and evolution, as well as the need for system explainability, validation and exploration boundaries constitutes the main motivation and unique characteristic of this workshop. Submissions are expected to focus on at least one of the following main topics:

A. Autonomous Learning Behaviour in Technical Systems, e.g. Active Learning, Transfer Learning, Online Concept Drift/Shift and Novelty/Obsoleteness Detection, Reinforcement Learning from Feedback, Transductive Inference for Efficient Model Building, Self-Awareness, …

B. Self-Adaptaion@Runtime, e.g. Automated Algorithm Configuration & Selection, Evolutionary Computation as Mechanism to Change, Context-aware and Transient Interfaces, …

C. Metrics and Quantification, e.g. for System Validation, Guaranteeing, Understanding & Trust, …

 

Important Dates

Based on the currently available schedule for the ARCS conference, we expect the following schedule for SAOS:

Paper submission deadline	15 February 2019
Decision notification	15 March 2019
Camera-ready version	29 March 2019

 

Submission

Papers should be in English and formatted according to IEEE CIS template in “conference mode”
(see http://www.ieee.org/conferences_events/conferences/publishing/templates.html).

Papers should not exceed 8 pages (full paper) or 4 pages (short paper).

PDF submission via EasyChair  https://easychair.org/conferences/?conf=saos2019

More details depend on the requirements given by the ARCS organisers and will be provided here as soon as possible.

 

Organisation & Technical Programme Committee

Organising Committee

 

	Anthony	Stein	Universität Augsburg (DE)	Official Website
	Sven	Tomforde	Universität Kassel (DE)	Official Website
	Jean	Botev	University of Luxembourg (LU)	Official Website
	Peter	Lewis	Aston University (UK)	Official Website

 

Advisory Board

 

Jörg	Hähner	Universität Augsburg (DE)
Christian	Müller-Schloer	Leibniz University Hannover (DE)
Bernhard	Sick	Universität Kassel (DE)

 

Programme Committee (tentative)

 

Kirstie	Bellman	Topcy House Consulting
Jean	Botev	University of Luxembourg
Uwe	Brinkschulte	University of Frankfurt
Ada	Diaconescu	Telecom ParisTech
Lukas	Esterle	Aston University
Jörg	Hähner	University of Augsburg
Heiko	Hamann	University of Luebeck
Martin	Hoffmann	Bielefeld University of Applied Sciences
Christian	Krupitzer	University of Würzburg
Chris	Landauer	Topcy House Consulting
Peter	Lewis	Aston University
Erik	Maehle	University of Luebeck
Gero	Mühl	University of Rostock
Christian	Müller-Schloer	Leibniz University Hannover
Christian	Renner	University of Luebeck
Stefan	Rudolph	University of Augsburg
Hella	Ponsar	University of Augsburg
Wolfgang	Reif	University of Augsburg
Ingo	Scholtes	University of Zurich
Bernhard	Sick	Universität Kassel
Anthony	Stein	University of Augsburg
Claudio Juan	Tessone	University of Zurich
Sven	Tomforde	University of Kassel
Sebastian	von Mammen	University of Würzburg
Torben	Weis	University of Duisburg-Essen