Connectionism vs AI

[James L. McClelland]

Regarding Worth's query about a possible fundamental opposition
between connectionist and other approaches to AI: I do not think there
need be such an opposition.  That is, I think one can be a
connectionist without imagining that any such opposition exists.

Connectionist models are used for a variety of different
purposes and with a variety of different goals in mind:

Here are three:

1) To find better methods for solving AI problems, particularly those that have
proven difficult to solve using conventional AI approaches.

2) To model actual mechanisms of neural computation.  There's lots of
data on such things as the stimulus conditions under which particular
neurons will fire, but there is little understanding of the circuitry
that leads to the patterns of firing that are seen or the role the
neurons play in overall system function.  Connectionist models can
help in the exploration of these questions.

3) To explore mechanisms of human information processing.  Here the
idea is that there is a set of putative principles of human
information processing that are more easily captured in connectionist
models than in other formalisms.  The effort to determine whether
these principles are the right ones or not requires the use of models,
since it is difficult to assess the adequacy of sets of principles
without formalization, leading to analysis and/or simulation.

There are others.

The point is that the models can be viewed as tools for exploring
questions.  There need be no such religion as 'connectionism'; all it
takes to be a connectionist is to find connectionist models useful.

-- Jay McClelland