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System Architecture

Incremental hierarchical architectures

In biology, hierarchical systems are the basis for the mental and behavioral capabilities of humans and higher animals. They facilitate a cognitive unloading of well understood behavior patterns to lower levels of control for freeing higher mental capacities. Furthermore, they allow an abstraction from direct sensory measurements and control sequences into associations and symbols for stably grounded intelligence.
We have formulated a language for incremental hierarchical systems including mathematical proofs for a successful layered decomposition and construction. Applications in robotics and automotive systems demonstrate that the incremental implementation reduces overall design effort and increases stability.

System Architecture

A system architecture describes the interplay and relations of a number of elements that together create a defined output. It allows e.g. for easy analysis, control of dependencies and  computational timing requirements. In particular, for systems consisting of modules of different types or origins, the system architecture plays an important role.
The theoretical analysis of system architectures is important for constructing increasingly complex systems. It becomes mandatory for the design of general architectures, as required e.g. for building autonomous systems.

The most prominent questions when researching system architectures are:
•     Can general beneficial decompositions be found  that facilitate incremental composition
with respect to functions, stability, testability, maintainability, re-use and even certifiability?
•     Can we find a series of abstractions for perceptions and  behaviors that allow researchers to focus on their specific challenge without the necessity to consider all technological dependencies in detail?

•     Can we provide scientific models that guarantee specific requirements by means of the design process rather than by tedious testing andvalidation?



For more information

C. Goerick, “Towards an understanding of hierarchical  architecture”,
IEEE Trans. Auton. Mental Develop., vol. 3, no. 1, pp. 54-63, 2011.

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