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Organic computing is a form of biologically-inspired computing with organic properties. It has emerged recently as a 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 new 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 such systems "organic". Hence, an "Organic Computing System" is a technical system which adapts dynamically to exogenous and endogenous change. It is characterized by self-X or self-* properties:
- self-configuration (auto-configuration),
- self-optimization (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. It can be seen as an extension of the Autonomic computing vision of IBM.
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. Organic computing can also be defined by biological processing systems. The ever expanding power of the processor(silicon based) will eventually hit a physical limit, due to the fact that you can make a, correctly functioning, silicon chip only so small. Using Organic compounds, not much different from the brain tissue that controls us, will be the only way to effectively continue growing our computing infrastructure in the future.
There is a multitude of self-* properties. The top most so called CHOP (for Configuration, Healing, Organization and Protection) are extended by the self-explanation and context-awareness.
Self-organization subsumes all other self-* properties, as they are all needed for a system to be self-organizing.
Self-configuration can be seen as the ability to set up the parameters of the system under study.
Self-optimizing might be seen as the ability to search more efficient ways of solving problems. Automatic monitoring and control of resources to ensure the optimal functioning with respect to the defined requirements;
Self-healing can be seen as the ability to recover from malfunctioning.
Self-protection might be considered as a subproperty of self healing, but with the difference of protecting against malicious attacks.
Self-explanation has two parts which are necessary for a system to account for the property of self-expaining:
- The ability to self-explain unknown concepts to one self. Thus being able to crate a internal representation (meaning or knowledge representation) using external information sources. This is equivalent with creating a Connotation and Denotation for a conceptualisation.
- The ability to transferring the internal representation to others. This is the ability of expressing the internal representation to others so that they can integrate this meaning into their knowledge representation and crate a Connotation and Denotation
Self-explanation represents the ability to communicate properties about oneself and one's abilities to others . There are two main areas of self-explanation:
- The explanation for an artificial reasoner
- The explanation for humans
Depending on the use case, self-explaining systems possess one or both of these self-explanatory properties.
Context-Awareness is the ability to react to endogenous and exogenous change in the system. It can be seen as a basis of adaptive systems.
First steps towards adaptive and self-organizing computer systems are already being undertaken.
Current research topics include: Adaptivity, reconfigurability, emergence of new properties, self-organization and self-explanation.
In a variety of research projects the priority research program SPP 1183 of the German Research Foundation (DFG) addresses fundamental challenges in the design of Organic Computing systems; its objective is a deeper understanding of emergent global behavior in self-organizing systems and the design of specific concepts and tools to support the construction of Organic Computing systems for technical applications.
- Müller-Schloer, Christian; v.d. Malsburg, Christoph and Würtz, Rolf P. Organic Computing. Aktuelles Schlagwort in Informatik Spektrum (2004) pp. 332-336.
- Müller-Schloer, Christian. Organic Computing – On the Feasibility of Controlled Emergence. CODES + ISSS 2004 Proceedings (2004) pp 2-5, ACM Press, ISBN 1-58113-937-3.
- Rochner, Fabian and Müller-Schloer, Christian. Emergence in Technical Systems. it Special Issue on Organic Computing (2005) pp. 188-200, Oldenbourg Verlag, Jahrgang 47, ISSN 1611-2776.
- Schmeck, Hartmut. Organic Computing – A New Vision for Distributed Embedded Systems. Proceedings of the Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC’05) (2005) pp. 201-203, IEEE, IEEE Computer Society 2005.
- Würtz, Rolf P. (Editor): Organic Computing (Understanding Complex Systems). Springer, 2008. ISBN 978-3642096426.
- DFG SPP 1183 Organic Computing
- Position Paper Organic Computing (German)
- Self-Organising Systems (SOS) FAQ
- The Organic Computing Page
- The PUPS/P3 Organic Computing Environment for Linux (Free Software)
- SeSAm Multiagent simulator and graphical modelling environment. (Free Software)
- Fähndrich, Johannes and Ahrndt, Sebastian and Albayrak, Sahin, "Towards Self-Explaining Agents", Advances in Intelligent Systems and Computing (2013)