Technical Report available: High-Level Perception

[David Chalmers]

The following paper is available electronically from the Center for Research
on Concepts and Cognition at Indiana University.

             HIGH-LEVEL PERCEPTION, REPRESENTATION, AND ANALOGY:
              A CRITIQUE OF ARTIFICIAL INTELLIGENCE METHODOLOGY

       David J. Chalmers, Robert M. French, and Douglas R. Hofstadter

                Center for Research on Concepts and Cognition
                             Indiana University
                                 CRCC-TR-49

High-level perception -- the process of making sense of complex data at an
abstract, conceptual level -- is fundamental to human cognition.  Via
high-level perception, chaotic environmental stimuli are organized into mental
representations which are used throughout cognitive processing.  Much work in
traditional artificial intelligence has ignored the process of high-level
perception completely, by starting with hand-coded representations.  In this
paper, we argue that this dismissal of perceptual processes leads to distorted
models of human cognition.  We examine some existing artificial-intelligence
models -- notably BACON, a model of scientific discovery, and the
Structure-Mapping Engine, a model of analogical thought -- and argue that
these are flawed precisely because they downplay the role of high-level
perception.  Further, we argue that perceptual processes cannot be separated
from other cognitive processes even in principle, and therefore that such
artificial-intelligence models cannot be defended by supposing the existence
of a "representation module" that supplies representations ready-made.
Finally, we describe a model of high-level perception and analogical thought
in which perceptual processing is integrated with analogical mapping, leading
to the flexible build-up of representations appropriate to a given context.

N.B. This is not a connectionist paper in the narrowest sense, but the 
representational issues discussed are very relevant to connectionism, and
the advocated integration of perception and cognition is a key feature
of many connectionist models.  Also, philosophical motivation for the
"quasi-connectionist" Copycat architecture is provided.

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This paper may be retrieved by anonymous ftp from cogsci.indiana.edu
(129.79.238.6).  The file is cfh.perception.ps.Z, in the directory pub.
To retrieve, follow the procedure below.

unix> ftp cogsci.indiana.edu                         # (or ftp 129.79.238.6)
ftp> Name: anonymous
ftp> Password: [identification]
ftp> cd pub
ftp> binary
ftp> get cfh.perception.ps.Z
ftp> quit
unix> uncompress cfh.perception.ps.Z
unix> lpr -P(your_local_postscript_printer) cfh.perception.ps

If you do not have access to ftp, hardcopies may be obtained by sending e-mail
to dave at cogsci.indiana.edu.