Organic computing is a form of biologically-inspired computing with organic properties. It has emerged recently as a challenging vision for future information processing systems. Organic Computing is based on the insight that we will soon be surrounded by large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicate freely, and organise themselves in order to perform the actions and services that seem to be required.
The 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 such systems — which we increasingly depend on — as robust, safe, flexible, and trustworthy as possible. In particular, a strong orientation 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 lifelike 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 is characterised by the self-X properties:
- self-configuration (auto-configuration),
- self-optimisation (automated optimization),
- self-protection (automated computer security),
- and context-awareness.
The vision of Organic Computing and its fundamental concepts arose independently in different research areas like Neuroscience, Molecular Biology, and Computer Engineering.
Self-organising 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.
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