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

these states. This relationship is a basic property of a physical symbol system, and is
called designation (Newell, 1980; Newell & Simon, 1976). “An expression designates
an object if, given the expression, the system can either affect the object itself or
behave in ways dependent on the object” (Newell & Simon, 1976, p. 116).
Explaining designation is a controversial issue in cognitive science and philosophy.
There are many different proposals for how designation, which is also called
the problem of representation (Cummins, 1989) or the symbol grounding problem
(Harnad, 1990), occurs. The physical symbol system hypothesis does not propose
a solution, but necessarily assumes that such a solution exists. This assumption is
plausible to the extent that computers serve as existence proofs that designation
is possible.
The second semantic property of a physical symbol system is that not only are
individual expressions meaningful (via designation), but the evolution of expressions—the
rule-governed transition from one expression to another—is also meaningful.
That is, when some operation modifies an expression, this modification is
not only syntactically correct, but it will also make sense semantically. As rules
modify symbolic structures, they preserve meanings in the domain that the symbolic
structures designate, even though the rules themselves are purely formal. The
application of a rule should not produce an expression that is meaningless. This
leads to what is known as the formalist’s motto: “If you take care of the syntax, then
the semantics will take care of itself ” (Haugeland, 1985, p. 106).
The assumption that applying a physical symbol system’s rules preserves meaning
is a natural consequence of classical cognitive science’s commitment to logicism.
According to logicism, thinking is analogous to using formal methods to derive a
proof, as is done in logic or mathematics. In these formal systems, when one applies
rules of the system to true expressions (e.g., the axioms of a system of mathematics
which by definition are assumed to be true [Davis & Hersh, 1981]), the resulting
expressions must also be true. An expression’s truth is a critical component of its
semantic content.
It is necessary, then, for the operations of a formal system to be defined in
such a way that 1) they only detect the form of component symbols, and 2) they are
constrained in such a way that manipulations of expressions are meaningful (e.g.,
truth preserving). This results in classical cognitive science’s interest in universal
machines.
A universal machine is a device that is maximally flexible in two senses (Newell,
1980). First, its behaviour is responsive to its inputs; a change in inputs will be capable
of producing a change in behaviour. Second, a universal machine must be able
compute the widest variety of input-output functions that is possible. This “widest
variety” is known as the set of computable functions.
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