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Functional Analysis Functional analysis is a methodology that is used to explain the workings of a complex system. The basic idea is that the system is viewed as computing a function (or, more generally, as solving an information processing problem). Functional analysis assumes that such processing can be explained by decomposing this complex function into a set of simpler functions that are computed by an organized system of subprocessors. The hope is that when this type of decomposition is performed, the subfunctions that are defined will be simpler than the original function, and as a result will be easier to explain. A very detailed treatment of functional analysis is provided by Cummins (1983). He proposes a three-stage methodology that defines functional analysis. In the first stage, the to-be-explained function is defined. In the second stage, analysis is performed. The to-be-explained function is decomposed into an organized set of simpler functions. This analysis can proceed recursively by decomposing some (or all) of the subfunctions into sub-subfunctions. In the third stage, analysis is stopped by subsuming the bottom level of functions. This means that the operation of each of these operation is explained by appealing to natural laws (e.g., mechanical or biological principles). If functional analysis is applied to an information processing system, then the level of subsumed functions defines the functional architecture for that information processor. Functional analysis is important to cognitive science because it offers a natural methodology for explaining how information processing is being carried out. For instance, any "black box diagram" offered as a model or theory by a cogntive psychologist represents the result of carrying out the analytic stage of functional analysis. Any proposal about what constitutes the cognitive architecture can be viewed as a hypothesis about the nature of cognitive functions at the level at which these functions are subsumed. References:
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