Adaptivity and self-organization in organic computing systems

Abstract

Organic Computing (OC) and other research initiatives like Autonomic Computing or Proactive Computing have developed the vision of systems possessing life-like properties: they self-organize, adapt to their dynamically changing environments, and establish other so-called self-x properties, like self-healing, self-configuration, self-optimization, etc. What we are searching for in OC are methodologies and concepts for systems that allow to cope with increasingly complex networked application systems by introduction of self-x properties and at the same time guarantee a trustworthy and adaptive response to externally provided system objectives and control actions. Therefore, in OC, we talk about controlled self-organization . Although the terms self-organization and adaptivity have been discussed for years, we miss a clear definition of self-organization in most publications, which have a technically motivated background. In this article, we briefly summarize the state of the art and suggest a characterization of (controlled) self-organization and adaptivity that is motivated by the main objectives of the OC initiative. We present a system classification of robust, adaptable, and adaptive systems and define a degree of autonomy to be able to quantify how autonomously a system is working. The degree of autonomy distinguishes and measures external control that is exerted directly by the user ( no autonomy ) from internal control of a system which might be fully controlled by an observer/controller architecture that is part of the system ( full autonomy ). The quantitative degree of autonomy provides the basis for characterizing the notion of controlled self-organization. Furthermore, we discuss several alternatives for the design of organic systems.

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