ONT Re: Inference, Information, Inquiry
¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤
Howard, John, Mishtu, Stan, Sung, OCAsional Readers,
Here is a passage from an old essay of mine that
comes to mind in regard to issues recently risen.
¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤
| Document History:
|
| Project: Intelligent Dynamic Systems Engineering
| Subject: Systems Engineering Interest Statement
| Contact: Jon Awbrey <jawbrey@oakland.edu>
| Version: 6.0
| Created: 12-Nov-1991
| Revised: 01-Sep-1992
| Revised: 01-Sep-2001
| Setting: Oakland University, Rochester, Michigan, USA
| Excerpt: Section 1.2.3 Intro (Architecture of Inquiry)
1.2.3 Architecture of Inquiry
The outlines of one important landmark can already be seen from this station.
It is the architecture of inquiry, in the style traced out by C.S. Peirce
and John Dewey on the foundation poured by Aristotle. I envision being
able to characterize the simplest drifts of its dynamics in terms of
certain differential operators.
It is important to remember that knowledge is a different sort of goal from
the run-of-the-mill setpoints that a system might have. The typical goal is
a state that a system has actively experienced many times before, like normal
body temperature for a human being. But a particular state of knowledge that
an intelligent system moves toward may be a state that it has never been through
before. The fundamental equivocation on this point expressed in Plato's 'Meno',
whether learning is functionally equivalent to remembering, was discussed above.
In spite of this quibble, it still seems necessary to regard states of knowledge
as a distinctive class. The reasons for this may lie in the fact that a useful
definition of inquiry for human beings necessarily involves a whole community
of inquiry.
On account of this social character of inquiry, even those states
of knowledge that might be arrived at through accidental, gratuitous,
idiosyncratic, transcendental, or otherwise inexplicable means are
useless for most human purposes unless they can be communicated,
that is, reliably reproduced in the social system as a whole.
In order to do this it seems necessary as a practical matter,
whatever may have been the original process of construction,
that such states of knowledge be obtainable through the option
of a rational reconstruction. Hence the familiar requirement of
proof for mathematical results, no matter how inspired their first
glimmerings. Hence the discipline of programming that challenges
workers in AI to represent intelligent processes in terms of
computable functions, however differently intelligence may
have evolved in the frame of biological time.
Aristotle long ago pointed out that there can be no genuine science
of the absolutely isolated event, no systematic knowledge of the purely
and totally idiosyncratic subject matter. Science does not have as its
domain all of experience but only that fraction which is indefinitely
repeatable. Likewise, on the negative branch, concerning the lack of
knowledge that occasions a problem, a state that never recurs does not
present a problem for a system. This limitation of scientific problems
and knowledge to recurrent phenomena yields up a very significant clue:
The placement of intelligence and knowledge in analogy with systematic
attributes like frequency and momentum may turn out to be based on
deeply common principles.
¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤~~~~~~~~~¤