Pylyshyn
argues that for purposes of cognitive science, there is a fundamental
difference between the cognitive architecture and other levels of the system.
The architecture acts as the realization of a theory of cognition, and
without an architecture defined independently from other aspects of the
system, the computational model of that theory cannot claim to be a literal model of a
cognitive process. (This is surely a cognitive science approach, in which
computational models are hoped to explain cognitive processes.) From this
argument, he extends three reasons as a basis for this view:
Architecture-relativity of algorithms and strong equivalence
We can design an algorithm that corresponds to a specific cognitive process
only when we have first made relevant assumptions about the architecture.
Architecture as a theory of cognitive capacity
The architecture provides cognitive constants (namely, capacity), while
the algorithms provide parameters decreed by the information coming in.
Architecture as marking the boundary of representation-governed
processes
A general assumption in cognitive science is that there is a domain of
mental phenomena that can be explained in terms of representations and
functions that operate over those representations (i.e., this is a
cognitive science version of the
physical symbol system hypothesis).
Furthermore, these
processes remain invariant over changes in goals and knowledge. From this,
it is suggested that the architecture must be
cognitively impenetrable.
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