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

Miller, 2009; Miller & Shettleworth, 2007, 2008; Nolfi, 2002). As a result, the modularity
of geometric cue processing is being seriously re-evaluated (Cheng, 2008).
In summary, many researchers agree that the architecture of cognition is
modular. A variety of different kinds of evidence can be marshaled to support the
claim that some function is modular and therefore part of the architecture. This
evidence is different from, and can complement, evidence about cognitive penetrability.
Establishing the nature of the architecture is nonetheless challenging and
requires combining varieties of evidence from behavioural and cognitive neuroscientific
studies.
3.15 Reverse Engineering
Methodologically speaking, what is classical cognitive science? The goal of classical
cognitive science is to explain an agent’s cognitive abilities. Given an intact,
fully functioning cognitive agent, the classical cognitive scientist must construct a
theory of the agent’s internal processes. The working hypothesis is that this theory
will take the form of a physical symbol system. Fleshing this hypothesis out will
involve proposing a theory, and hopefully a working computer simulation, that will
make explicit proposals about the agent’s symbol structures, primitive processes,
and system of control.
Given this scenario, a classical cognitive scientist will almost inevitably engage
in some form of reverse engineering.
In reverse engineering, one figures out what a machine was designed to do. Reverse
engineering is what the boffins at Sony do when a new product is announced by
Panasonic, or vice versa. They buy one, bring it back to the lab, take a screwdriver
to it, and try to figure out what all the parts are for and how they combine to make
the device work. (Pinker, 1997, p. 21)
The reverse engineering conducted by a classical cognitive science is complicated by
the fact that one can’t simply take cognitive agents apart with a screwdriver to learn
about their design. However, the assumption that the agent is a physical symbol
system provides solid guidance and an effective methodology.
The methodology employed by classical cognitive science is called functional
analysis (Cummins, 1975, 1983). Functional analysis is a top-down form of reverse
engineering that maps nicely onto the multiple levels of investigation that were
introduced in Chapter 2.
Functional analysis begins by choosing and defining a function of interest to
explain. Defining a function of interest entails an investigation at the computational
level. What problem is being solved? Why do we say this problem is being
solved and not some other? What constraining properties can be assumed to aid the
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