<Bob Clark (940427.1556 EDT)>
Bill Powers (940422.0600 MDT) Subject: predictions; DME
This was the fifth topic in your post. To simplify the discussion, I
am experimenting with trying to keep each post to a single topic.
In your post you say:
we have to guard against letting the modeling process degenerate
into an unprincipled taxonomy. There are unnumerable ways of
classifying perceptions, with different approaches slicing the pie
in different directions to create artificial categories.
In general, Bill, I agree with this. (I must point out, however,
that ANY category is artificial in the sense that it exists
exclusively in the brains (and writings) of humans.) Many of them are
useful to a limited degree, for limited purposes. That is to be
expected. The ultimate test is the extent to which people find them
useful. Categories structured on some idealized basis, even if
incomplete or incorrect, seem to offer greater probability for
acceptance than those containing internal inconsistencies and
contradictions.
The concept that later developed into PCT was an idealized hierarchy
of idealized negative feedback control systems.
In your post you have re-stated the hierarchical principle. This
principle is the key to the entire PCT structure:
the requirement that higher-level perceptions must be functions of
lower-level ones, and controlling a higher-level perception
requires altering lower-level ones.
PCT is unique in that it is "self-correcting." A set of negative
feedback control systems will tend to detect and correct errors,
contradictions, etc.
PCT is impressive because its basic concept is "generative" in the
sense that it readily incorporates additions, changes and revisions
without impairing its hierarchical structure. Its potential for
development and ultimate acceptance is similar to that of classical
mechanics, dynamics and their progeny.
This basis was originally conceived by you, Bill, during our
association. And you have further developed it into the present form
of PCT.
Regards, Bob Clark