Mind, Body, World- Foundations of Cognitive Science, 2013a

current PDP networks are not autonomous because their learning principles are
not in fact directly realized in the network architecture. That is, networks governed
by these principles require explicit signals from some external controller to determine
when they will learn or when they will perform a learned task. (Dawson and
Schopflocher 1992a, pp. 200–201)
This is not a principled limitation, for Dawson and Schopflocher presented a much
more elaborate architecture that permits a standard pattern associator to learn and
recall autonomously, that is, without the need for a user’s intervention. However,
this architecture is not typical; standard pattern associators like the one in Figure
4-1 demand executive control.
The need for such control is not limited to simple distributed memories. The
same is true for a variety of popular and more powerful multilayered network
architectures, including multilayered perceptrons and self-organizing networks
(Roy, 2008). “There is clearly a central executive that oversees the operation of the
back-propagation algorithm” (p. 1436). Roy (2008) proceeded to argue that such
control is itself required by brain-like systems, and therefore biologically plausible
networks demand not only an explicit account of data transformation, but also a
biological theory of executive control.
In summary, connectionist networks generally require the same kind of control
that is a typical component of a classical model. Furthermore, it was argued earlier
that there does not appear to be any principled distinction between this kind of control
and the type that is presumed in an embodied account of cognition. Control is a
key characteristic of a cognitive theory, and different schools of thought in cognitive
science are united in appealing to the same type of control mechanisms. In short,
central control is not a mark of the classical.
7.4 Serial versus Parallel Processing
Classical cognitive science was inspired by the characteristics of digital computers;
few would deny that the classical approach exploits the digital computer metaphor
(Pylyshyn, 1979a). Computers are existence proofs that physical machines are capable
of manipulating, with infinite flexibility, semantically interpretable expressions
(Haugeland, 1985; Newell, 1980; Newell & Simon, 1976). Computers illustrate how
logicism can be grounded in physical mechanisms.
The connectionist and the embodied reactions to classical cognitive science
typically hold that the digital computer metaphor is not appropriate for theories of
cognition. It has been argued that the operations of traditional electronic computers
are qualitatively different from those of human cognition, and as a result the
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