January 15 – 20 , 2006, Dagstuhl Seminar 06031

Organic Computing - Controlled Emergence


Kirstie Bellman (The Aerospace Corp. – Los Angeles, US)
Peter Hofmann (Daimler Research – Stuttgart, DE)
Christian Müller-Schloer (Leibniz Universität Hannover, DE)
Hartmut Schmeck (KIT – Karlsruhe, DE)
Rolf P. Würtz (Ruhr-Universität Bochum, DE)

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Organic Computing has emerged recently as a challenging vision for future information processing systems, based on the insight that it won’t be long before we are surrounded by large collections of autonomous systems equipped with sensors and actuators to be aware of their environment, to communicate freely, and to organize themselves in order to perform the actions and services that seem to be required. This presence of networks of intelligent systems in our environment opens fascinating application areas but, at the same time, bears the problem of their controllability. Hence, we have to construct these systems - which we increasingly depend on - as robust, safe, flexible, and trustworthy as possible. In particular, a strong orientation of these systems towards human needs as opposed to a pure implementation of the technologically possible seems absolutely central. In order to achieve these goals, our technical systems will have to act more independently, flexibly, and autonomously, i.e. they will have to exhibit life-like properties. We call those systems "organic". Hence, an "Organic Computing System" is a technical system, which adapts dynamically to the current conditions of its environment. It will be self-organizing, self-configuring, self-healing, self-protecting, self-explaining, and context-aware.

The vision of Organic Computing and its fundamental concepts arose independently in different research areas like Neuroscience, Molecular Biology, and Computer Engineering. Self-organizing systems have been studied for quite some time by mathematicians, sociologists, physicists, economists, and computer scientists, but so far almost exclusively based on strongly simplified artificial models. Central aspects of Organic Computing systems have been and will be inspired by an analysis of information processing in biological systems. Nevertheless, the anticipated first generation of organic computing systems will still be based on well known silicon technology. Their life-like properties will arise from opening up certain degrees of freedom in the functionality of technical application systems and by the transfer of organisational concepts observable in natural systems into their system architecture.

This Dagstuhl seminar was meant as a forum for scientists from various disciplines working on key aspects of “Organic Computing” or on closely related concepts. Its objective was to initiate cooperative research on the major challenges of this vision of tomorrow’s informatics systems. Although the occurrence of emergence has been welldocumented in previous papers and conferences, the seminar addressed the new challenge of combining processes leading to emergence with system engineering. The challenge of “Controlled Emergence” is the possible contradiction of free running emergent processes generating new and unexpected results on the one hand, and the requirement of system engineering to design and manage a system with emergent properties in order to guarantee desired system behaviors and to avoid unwanted sideeffects. These problems have been discussed from the perspective of different neighbouring disciplines (like physics, chemistry, biology) and computer science with the objective of investigating the applicability of selforganizing and emergent mechanisms to technical systems.

The Results

The crosscutting themes of the seminar were intensive discussions on the exact meaning of the terms selforganization and emergence, with the accompanying emphasis on creating not only better theoretical foundations for the use of these terms, but also better operational definitions, methods, and measurements of emergence and related phenomena. While no concise final definition could be reached, the terms have been narrowed down to a more practical and touchable meaning, excluding nonscientific notions of emergence and focusing on quantitative approaches.

More in

Dagstuhl Seminar Series


  • Artificial Intelligence / Robotics
  • Modelling / Simulation
  • Networks
  • Hardware
  • Interdisciplinary (e.g. Bioinformatics)


  • Organic computing
  • Autonomous units
  • Emergence
  • Adaptive systems


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