Cognitive science is the interdisciplinary study of mind and intelligence,
embracing philosophy, psychology, artificial intelligence, neuroscience,
linguistics, and anthropology. Its intellectual origins are in the mid-1950s
when researchers in several fields began to develop theories of mind based
on complex representations and computational procedures. Its organizational
origins are in the mid-1970s when the Cognitive Science Society was formed
and the journal Cognitive Science began. Since then, more than sixty universities
in North America and Europe have established cognitive science programs
and many others have instituted courses in cognitive science.
Teaching an interdisciplinary course in cognitive science is difficult because
students come to it with very different backgrounds. Since 1993, I have
been teaching a popular course at the University of Waterloo called Introduction
to Cognitive Science. On the one hand, the course attracts computationally
sophisticated students from computer science and engineering who know little
psychology or philosophy; on the other, it attracts students with good backgrounds
in psychology or philosophy but who know little about computation. This
text is part of an attempt to construct a course that presupposes no special
preparation in any of the fields of cognitive science. It is intended to
enable students with an interest in mind and intelligence to see that there
are many complementary approaches to the investigation of mind.
There are at least three different ways to introduce cognitive science to
a multidisciplinary audience. The first is to concentrate on the different
fields of psychology, artificial intelligence, and so on. The second is
to organize the discussion by different functions of mind, such as problem
solving, memory, learning, and language. I have chosen a third approach,
systematically describing and evaluating the main theories of mental representation
that have been advocated by cognitive scientists, including logic, rules,
concepts, analogies, images, and connections (artificial neural networks).
Discussing these fundamental theoretical approaches provides a unified way
of presenting the accomplishments of the different fields of cognitive science
to understanding various important mental functions.
My goal in writing this book is to make it accessible to all students likely
to enroll in an introduction to cognitive science. Accomplishing this goal
requires, for example, explaining logic in a way accessible to psychology
students, computer algorithms in a way accessible to English students, and
philosophical controversies in a way accessible to computer science students.
Feedback about failures of intelligibility will be greatly appreciated.
While this book is intended for undergraduates, it should also be useful
for graduate students and faculty who want to see how their own fields fit
into the general enterprise of cognitive science. I have not written an
encyclopedia. Since the whole point of this exercise is to provide an integrated
introduction, I have kept the book relatively short and to the point, highlighting
the forest rather than the trees. Viewing cognitive science as the intersection
rather than as the union of all the relevant fields, I have omitted many
topics that are standard in introductions to artificial intelligence, cognitive
psychology, philosophy of mind, and so on. Each chapter concludes with a
summary and suggestions for further reading.
The book is written with great enthusiasm for what theories of mental representation
and computation have contributed to the understanding of mind, but also
with awareness that cognitive science has a long way to go. The second part
of the book discusses challenges to the basic assumptions of cognitive science
and suggests directions for future interdisciplinary work.