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Enzymatic computation and cognitive modularity H Clark Barrett, University of California, Los Angeles
ABSTRACT: Currently, there is widespread skepticism that higher cognitive processes, given their apparent flexibility
and globality, could be carried out by specialized computational devices, or modules. This skepticism is largely due to
Fodor's influential definition of modularity. From the rather flexible catalogue of possible modular features that
Fodor originally proposed has emerged a widely held notion of modules as rigid, informationally encapsulated devices
that accept highly local inputs and whose operations are insensitive to context. It is a mistake, however, to equate
such features with computational devices in general and therefore to assume, as Fodor does, that higher cognitive
processes must be non-computational. Of the many possible non-Fodorean architectures, one is explored here that offers
possible solutions to computational problems faced by conventional modular systems: an 'enzymatic' architecture.
Enzymes are computational devices that use lock-and-key template matching to identify relevant information
(substrates), which is then operated upon and returned to a common pool for possible processing by other devices.
Highly specialized enzymes can operate together in a common pool of information that is not pre-sorted by information
type. Moreover, enzymes can use molecular 'tags' to regulate the operations of other devices and to change how
particular substrates are construed and operated upon, allowing for highly interactive, context-specific processing.
This model shows how specialized, modular processing can occur in an open system, and suggests that skepticism about
modularity may largely be due to failure to consider alternatives to the standard model.
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