🚀 go-pugleaf

I have been studying linguistics and cognitive science type stuff for
about two years in college, and I am just now becoming aware of the
long line of cybernetic thought which runs parallel to "good
old-fashioned" symbolic AI. Why is this work now (and apparently
always since the schism) more obscure than work done in symbolic,
serial cognitive modelling?

I quote from _Foundations of Neural Networks_ by Tarun Khanna
(Addison-Wesley 1990):

#This continuous/symbolic dichotomy gave rise to and was then
#reinforced by other concurrently existing dichotomies. The
#cyberneticians dealt primarily with pattern recognition and were
#concerned with developing systems that learned. The AI community, on
#the other hand, concentrated on problem solving and therefore on
#creating systems that performed specific tasks demanding intelligence,
#for example, theorem-proving and game-playing. Predictably, each of
#these groups of tasks was easier to tackle in its specific class of
#systems. For example, it is easier to tackle a game-playing exercise
#in a programming system than in a continuous system. Simultaneously,
#cyberneticians were preoccupied with the neurophysiology and the AI
#community with psychology. While the former connection is easier to
#understand, the latter arose primarily because it is easier to
#postulate psychologically meaningful results using programming systems
#than it is to postulate physiological ones. Their preoccupation with
#neurophysiology led cyberneticians to deal primarily with highly
#parallel systems. The programming systems employed by the AI community
#were, on the other hand, inherently serial. (page 4)

[Khanna goes on to portray connectionism as a new hybrid between the
two traditions.]

I am amazed that this alternative to symbolic AI is so obscure. Why
are (symbolic) artificial intelligence classes, theories and opinions
so easy to find, but cybernetic thought has faded away, become
esoteric? 

There are lots of reasons I can think of which seem reasonable, but I
don't know enough of the history to be sure:

* Cybernetic theory is more abstract, difficult, vague. (No idea yet
  if this is even true.)

* The "Chomskyan Revolution" in linguistics and/or the "Cognitive
  Revolution" in psychology tipped the scales in the symbolic AI
  tradition's favor. (No idea what the causal relationships are
  between the three symbolic schools, if any can be clearly
  attributed.)

* The foundations of serial programming caught on before the
  foundations of parallel programming (which we are still hammering
  out today, imho), so applications of symbolic AI were more
  successful, more glamorous, sooner.

Does anyone have any thoughts on this?

Jake.
-- 
* What's so interdisciplinary about studying lower levels of thought process?
				  <-- Jacob Galley * gal2@midway.uchicago.edu