In the beginning, there was language, and it was good.
Then two eminent scholars debated its origin, and this debate
gave rise to the
. . .
Like most approaches to the mind, cognitive science can be traced back to philosophical
questions, especially about the nature of knowledge. For instance,
, where he
investigates the source of knowledge, can be seen as a foundational text.
The modern culture of cognitive science can be traced back to the early
1930s and 1940s, such as
, who sought to understand the
organizing principles of the mind . McCulloch and Pitts essentially invented the
but did not have the computational tools to develop it into modern form.
Another precursor was the early development of the
theory of computation
in the 1940s and 1950s.
John von Neumann
were instrumental in
these developments. The modern computer, or
Von Neumann machine
, would play a central role
in cognitive science, both as a metaphor for the mind, and as a tool for investigation.
published a scathing review of
B. F. Skinner
At the time, Skinner's
paradigm dominated psychology: Most psychologists focused
on functional relations between stimulus and response, without positing internal representations.
Chomsky's work showed that in order to explain language, we needed a theory like his
, which not only attributed internal representations but characterized their
underlying order. This hugely successful theory would inspire much later cognitive science.
In the 1970s and early 1980s, much cognitive science research focused on the possibility of
. Researchers such as
would write computer programs in
languages such as
to attempt to formally characterize the steps that human beings went
through, for instance, in making decisions and solving problems, in the hope of better
understanding human thought, and also in the hope of creating artificial minds. This approach is
known as "symbolic AI".
Eventually the limits of the symbolic AI research program became apparent. For instance, it
seemed to be unrealistic to comprehensively list human knowledge in a form usable by a
symbolic computer program. The late 80s and 90s saw the rise of
as a research paradigm. Under this point of view, often attributed to
, the mind could be characterized as a set of complex
associations, represented as a layered network. Critics argue that there are some phenomena
which are better captured by symbolic models, and that connectionist models are often so
complex as to have little explanatory power. But the flexibility and biological plausibility of
these models made them very successful.
Today a plurality of approaches exist, from connectionism, to a focus on dynamical systems