Teaching
the foundations of cognitive science requires providing students a sense of its
historical and philosophical roots. My
lectures try to accomplish this by providing heavy doses of quotes from, and
pictures of, pioneering cognitive scientists.
(I gathered enough of this material to launch a gallery of cognitive
scientists.)
Last
term, as part of my mission to expose students to the roots of cognitive
science, I found myself describing various pioneering works as ‘desert island
books’. I told my class that these were
classic texts that any marooned cognitive scientist would be content to have by
their side when facing a lengthy wait for rescue. I am not expecting to be in that situation
myself, but after 25 years at the University of Alberta I can comfortably
imagine retiring to my retreat at Hastings Lake, Alberta to spend some serious
time reading classics of cognitive science.
In addition, I am long enough in the tooth to be able to suggest a few foundational
texts for budding cognitive scientists.
What
books would provide me contentment on a desert island?
I
generated the list below to answer this question. I constrained it in two ways. First, I limited it to thirteen books. Second, I tried to give equal representation
to the three major approaches to cognitive science (classical, connectionist,
and embodied).
Classical Cognitive
Science
Miller,
G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the Structure Of
Behavior. New York: Henry Holt &
Co.
Newell,
A., & Simon, H. A. (1972). Human Problem Solving. Englewood Cliffs,
NJ: Prentice-Hall.
Pylyshyn,
Z. W. (1984). Computation and Cognition. Cambridge, MA.: MIT Press.
Simon,
H. A. (1969). The Sciences of the Artificial. Cambridge, MA: MIT Press.
About
25 years ago I rescued my copy of Miller, Galanter and Pribram from a discard
pile; after my first reading of it I was amazed at how current this pioneering
book still managed to be. A recent look
through it reminded me of its attempt to bridge cognitivism with
cybernetics. Newell and Simon provide an
incredible manifesto of modeling in a classic book that introduces production
systems, physical symbol systems, and protocol analysis. Pylyshyn’s book offers a rich theoretical
account of the implications of assuming that cognition is computation,
including a deep discussion of what is involved in validating models of
cognition. Simon’s masterpiece provides
a link between the science of cognition and the science of design, and is a
continuous source of inspiration about how to think like a cognitive scientist.
Connectionist
Cognitive Science
McCulloch,
W. S. (1988). Embodiments of Mind. Cambridge, MA: MIT Press.
Minsky,
M. L., & Papert, S. (1969). Perceptrons: An Introduction To
Computational Geometry (1st ed.). Cambridge, Mass.,: MIT Press.
Rosenblatt,
F. (1962). Principles of Neurodynamics. Washington: Spartan Books.
Rumelhart,
D. E., & McClelland, J. L. (1986). Parallel Distributed Processing, V.1.
Cambridge, MA: MIT Press.
The
McCulloch book is a collection of his important papers, primarily from the
1940s into the 1960s, many of which are classics. It is not an easy read, but it is fun, and it
is also incredible to see the breadth of topics covered – links from the
abstract to the physical abound. Minsky
and Papert provide a wonderfully challenging read that illustrates how
computational analyses of artificial neural networks should proceed. Rosenblatt’s magnum opus introduces the
perceptron, but is far deeper than some might expect, and foresees aspects of
the New Connectionism. The Rumelhart and
McClelland book heralded New Connectionism; this first volume of a pair of
books gives the reader a lot of dangerous information about how to carry out
connectionist research. (It is largely responsible for my developing my own
skills in this field; I suspect that many connectionists taught themselves from
reading it in the late 1980s.)
Embodied Cognitive
Science
Braitenberg,
V. (1984). Vehicles: Explorations in Synthetic Psychology. Cambridge,
MA: MIT Press.
Gibson,
J. J. (1979). The Ecological Approach To Visual Perception. Boston, MA:
Houghton Mifflin.
Neisser,
U. (1976). Cognition and Reality: Principles And Implications Of Cognitive
Psychology. San Francisco: W. H. Freeman.
Winograd,
T., & Flores, F. (1987). Understanding Computers and Cognition. New
York: Addison-Wesley.
This
is quite a mixed bag of selections, which is only proper, because the embodied
approach is fairly fragmented.
Braitenberg provides a collection of thought experiments that illustrate
the importance of realizing that an agent is embedded in its environment. It ties in nicely with the Simon book
mentioned earlier. Gibson’s theory of perception
is a foundational example of the key elements of embodied cognitive science,
and Gibson’s work inspired Neisser’s embodied treatment of cognition. Winograd and Flores offer a fascinating
critique of classical cognitive science, and suggest embodied solutions to
these problems. I read both Neisser and
Winograd and Flores when I was a student and missed the point of both books; 25
years later I was astounded with how prescient both were, and was amazed at my
inability to understand them properly on the first read!
Combining Elements Of
All Three Approaches
Marr,
D. (1982). Vision. San Francisco, Ca.: W.H. Freeman.
The
last book on my list is such a seminal work that it really stands on its
own. Furthermore, Marr’s theory combines
strong elements of all of the different schools of cognitive science: he is
clearly concerned with constructing representations in the classical sense, but
develops algorithms that are essentially connectionist, and his proofs concern
properties of the world (i.e. natural constraints). His ability to move from mathematical proofs
to single cell recordings of visual neurons is astonishing; for me, this was
one of the two most influential books that I have ever read (the other being
Pylyshyn’s, cited above).
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