Connectionist symbol processing: any progress?

[Bryan B. Thompson]

Hello,

We are currently engaged in cognitive modeling of reflexive
(recognitional) and reflective (metacognitive) behaviors.  To
this end, we have used a structured connectionist model of
inferential long-term memory, with good results.

The reflexive system is based on the Shruti model proposed by
Shastri and Ajjanagadde (1993, 1996).  Working with Shastri,
we have extended the model to incorporate supervised learning,
priming, etc.  We are currently working on an integration of belief
and utility within this model. The resulting network will be able
to not only reflexively construct interpretations of evidence from
its environment, but will be able to reflexively plan and execute
responses at multiple levels of abstraction as well.

The reflexive system is coupled to a metacognitive system, which
is responsible for directing the focus of attention, making and
testing assumptions, identifying and responding to conflicting
interpretations and/or goals, locating unreliable conclusions,
and managing risk.

The perspective that only a fully distributed representation represents
a connectionist solution to structure, variable binding, etc. is perhaps,
what warrents challange.  The brain is by no measure without internal
structure on both gross and very detailed levels.  While research has yet
to identify rich mechanisms for dealing with structured representations and
inference within a fully distributed representation, it has also
yet to fully explore the potential of specialized neural structures
for systematic reasoning.

-- bryan thompson
Cognitive Technologies, Inc.
bryan at cog-tech.com

References:

Thompson, B.B., Cohen, M.S., Freeman, J.T. (1995). Metacognitive behavior in
adaptive agents. In Proceedings of the World Congress on Neural Networks,
(IEEE, July).

Cohen, Marvin S. and Freeman, Jared T. (1996). Thinking naturally about
uncertainty. In Proceedings of the Human Factors & Ergonomics Society, 40th
Annual Meeting. Santa Monica, CA: Human Factors Society.