Monday, March 04, 2013

Desert Island Books For Cognitive Scientists

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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