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

and research agenda, breaking completely from traditional (symbolic) cognitive
theories. SA is not a new approach to cognition, much less a new school of cognitive
psychology. (Vera & Simon, 1993, p. 46)
We see later in this book that production systems provide an interesting medium
that can be used to explore the relationship between classical, connectionist, and
embodied cognitive science.
3.11 Weak Equivalence and the Turing Test
There are two fundamentals that follow from accepting the physical symbol system
hypothesis (Newell, 1980; Newell & Simon, 1976). First, general human intelligence
is the product of rule-governed symbol manipulation. Second, because they are universal
machines, any particular physical symbol system can be configured to simulate
the behaviour of another physical symbol system.
A consequence of these fundamentals is that digital computers, which are one
type of physical symbol system, can simulate another putative member of the same
class, human cognition (Newell & Simon, 1961, 1972; Simon, 1969). More than fifty
years ago it was predicted “that within ten years most theories in psychology will
take the form of computer programs, or of qualitative statements about the characteristics
of computer programs” (Simon & Newell, 1958, pp. 7–8). One possible
measure of cognitive science’s success is that a leading critic of artificial intelligence
has conceded that this particular prediction has been partially fulfilled
(Dreyfus, 1992).
There are a number of advantages to using computer simulations to study cognition
(Dawson, 2004; Lewandowsky, 1993). The difficulties in converting a theory
into a working simulation can identify assumptions that the theory hides. The
formal nature of a computer program provides new tools for studying simulated
concepts (e.g., proofs of convergence). Programming a theory forces a researcher
to provide rigorous definitions of the theory’s components. “Programming is, again
like any form of writing, more often than not experimental. One programs, just
as one writes, not because one understands, but in order to come to understand.”
(Weizenbaum, 1976, p. 108).
However, computer simulation research provides great challenges as well. Chief
among these is validating the model, particularly because one universal machine
can simulate any other. A common criticism of simulation research is that it is possible
to model anything, because modelling is unconstrained:
Just as we may wonder how much the characters in a novel are drawn from real
life and how much is artifice, we might ask the same of a model: How much is
based on observation and measurement of accessible phenomena, how much is
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