%A Prof. Andreas Schierwagen
%J Natural Computing
%T On Reverse Engineering in the Cognitive and Brain  Sciences
%X 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.
%N 1
%K         Brain
        Cognition
        Capacity
        Decompositional analysis
        Localization
        Linearity
        Modularization
        Column concept
        Reverse engineering
        Complex systems
        Modeling relation


%P 141-150
%V 11
%D 2012
%I Springer
%L cogprints8729

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