Complexity Engineering encompasses a set of approaches to engineering systems which are typically composed of various interacting entities often exhibiting self-* behaviours and emergence. The engineer or designer uses methods that benefit from the findings of complexity science and often considerably differ from the classical engineering approach of ‘divide and conquer’. This article provides an overview on some very interdisciplinary and innovative research areas and projects in the field of Complexity Engineering, including synthetic biology, chemistry, artificial life, self-healing materials and others. It then classifies the presented work according to five types of nature-inspired technology, namely: (1) using technology to understand nature, (2) nature- inspiration for technology, (3) using technology on natural systems, (4) using biotechnology methods in software engineering, and (5) using technology to model nature. Finally, future trends in Complexity Engineering are indicated and related risks are discussed.
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Various research initiatives try to utilize the operational principles of organisms and brains to develop alternative, biologically inspired computing paradigms and artificial cognitive systems. This article reviews key features of the standard method applied to complexity in the cognitive and brain sciences, i.e. decompositional analysis or reverse engineering. The indisputable complexity of brain and mind raise the issue of whether they can be understood by applying the standard method. Actually, recent findings in the experimental and theoretical fields, question central assumptions and hypotheses made for reverse engineering. Using the modeling relation as analyzed by Robert Rosen, the scientific analysis method itself is made a subject of discussion. It is concluded that the fundamental assumption of cognitive science, i.e. complex cognitive systems can be analyzed, understood and duplicated by reverse engineering, must be abandoned. Implications for investigations of organisms and behavior as well as for engineering artificial cognitive systems are discussed. Delete the scoop?
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