Abstract for CNLS Conference

[Stevan Harnad]

Here is the abstract for my contribution to the session on the
"Emergence of Symbolic Structures" at the 9th Annual International
Conference on Emergent Computation, CNLS, Los Alamos National Laboratory,
May 22 - 26 1989

      Grounding Symbols in a Nonsymbolic Substrate

	    Stevan Harnad
	    Behavioral and Brain Sciences
	    Princeton NJ

There has been much discussion recently about the scope and limits of
purely symbolic models of the mind and of the proper role of
connectionism in mental modeling. In this paper the "symbol grounding
problem" -- the problem of how the meanings of meaningless symbols,
manipulated only on the basis of their shapes, can be grounded in
anything but more meaningless symbols in a purely symbolic system -- is
described, and then a potential solution is sketched: Symbolic
representations must be grounded bottom-up in nonsymbolic
representations of two kinds:  (1) iconic representations are analogs
of the sensory projections of objects and events and (2) categorical
representations are learned or innate feature-detectors that pick out
the invariant features of object and event categories. Elementary
symbols are the names of object and even categories, picked out by
their (nonsymbolic) categorical representations. Higher-order symbols
are then grounded in these elementary symbols. Connectionism is a
natural candidate for the mechanism that learns the invariant features.
In this way connectionism can be seen as a complementary component in a
hybrid nonsymbolic/symbolic model of the mind, rather than a rival to
purely symbolic modeling. Such a hybrid model would not have an
autonomous symbolic module, however; the symbolic functions would
emerge as an intrinsically "dedicated" symbol system as a consequence
of the bottom-up grounding of categories and their names.