6th International Workshop on

"Self-Optimisation in Autonomic &
Organic Computing Systems"


Braunschweig, Germany, 09 - 10 April 2018


Call for Papers


Keynote Announcement

Kirstie L. Bellman, Topcy House Consulting

Dr. Kirstie Bellman has over thirty-five years of academic, industrial, and consulting experience in both laboratory research and the development of models and information architectures for large military and government programs. Her published research spans a wide range of topics in Cognitive Science, Neuroscience, and Computer Science. In addition to playing a leading role in the development of programs in the error analysis and the evaluation of Artificial Intelligence programs, her group did internationally recognized research in conceptual design environments, software integration and architectures, and 'enterprise evaluation'.  She started the VEHICLES project, an environment for the conceptual design of space systems that incorporates both conventional and artificial intelligence methods.  With Dr. Landauer, she started the Wrappings approach to system integration. While at DARPA, she extended the then new concept of Virtual Worlds to education, business and research environments. With a number of academic partners, she is also developing new mathematical approaches to the analysis of Virtual Worlds containing collaborating humans, artificial agents, and heterogeneous representations, models and processing tools. Lastly, she has been working on reflective architectures that use models to manage their own resources and to reason about appropriate behavior. Recently she is combining reflective architectures with European Organic Computing approaches that emphasize the self-organizational properties of biologically-inspired architectures and operating systems to develop new cyber-security approaches.





Scope of the Workshop

Initiatives such as Autonomic Computing (AC) and Organic Computing (OC), or the more general research field of self-adaptive and self-organising systems (SASO), are based on the insight that we are increasingly surrounded by large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicating freely, and organising themselves in order to perform the required actions and services in an adequate and robust manner. The resulting presence of networks of intelligent systems in our daily environment opens fascinating application areas but, at the same time, bears the problem of their controllability.

Hence, different design concepts (such as the MAPE cycle and the Observer/Controller framework) have been developed to allow for a self-organised control process at runtime that relieves the designer from specifying all possibly occurring situations and configurations within the design process. Instead, the system itself takes over responsibility to find proper reactions to perceived changes in the environmental conditions. As designers are not able to foresee all possibly occurring situations and circumstances the system will face during its operation time, the self-organisation process of the system has to pursue a steadily self-optimising behaviour. Self-optimising behaviour can be triggered at various levels of the system’s design, ranging from basic control architectures over self-organised coordination/collaboration methods as well as from domain-specific optimisation techniques to the application of machine learning algorithms. Furthermore, related topics such as trust and security in collaborative systems provide necessary concepts to enable self-optimising behaviour in SASO systems. In this workshop, we will discuss current research efforts that endeavour the establishment of self-optimising system behaviour. Thereby, a special focus will be set on observable trends and upcoming challenges, resulting from well-known issues of adjacent domains such as evolutionary optimisation or machine learning.

Contributions are expected to focus on at least one of the following categories:

A.   Architectural concepts for enabling self-optimising system behaviour
B.   Applied machine learning and optimisation algorithms to achieve  
C.   Novel application scenarios for self-optimising systems
D.   Current trends/challenges in the field of self-optimising interconnected


Important Dates

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

Paper submission deadline:            January 12th, 2018

Decision notification:                    January 26th, 2018

Camera-ready version:                 February 2nd, 2018

We assume that publications will be published by VDE as done for previous events.




Workshop organisation


Programme committee (to be completed)