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ARTIFICIAL_SIMON
January 31, 2022
At the outset in "The Sciences of the Artificial",
Herbert A. Simon begins with the insight that you
often understand the behavior of a large system
without any detailed understanding of its components.
"We knew a great deal about the gross physical and chemical
behavior of matter before we had a knowledge of molecules, a great
deal about molecular chemistry before we had an atomic theory, and
a great deal about atoms before we had any theory of elementary
particles if indeed we have such a theory today."
"This skyhook-skyscraper construction of science from the roof
down to the yet unconstructed foundations was possible because the
behavior of the system at each level depended on only a very
approximate, simplified, abstracted characterization of the system
at the level next beneath."
-- Herbert A. Simon
"The Sciences of the Artifical"
There's a footnote here where he quotes
Bertrand Russell from _Principia Mathematica_:
Simon presents this
"'... the chief reason in favour of any Russell quote as
theory on the principles of mathematics must saying something
always be inductive, i.e., it must lie in similar to his own--
the fact that the theory in question enables one also builds
us to deduce ordinary mathematics. In mathematics "from the
mathematics, the greatest degree of roof down", or so
self-evidence is usually not to be found Russell seems to
quite at the beginning, but at some later suggest here.
point; hence the early deductions, until
they reach this point, give reasons rather I interpret this a little
for believing the premises because true differently:
consequences follow from them, than for
believing the consequences because they THE_DOCTRINE_OF_POSTULATES
follow from the premises.'"
EPISTEMS
Simon comments:
"Contemporary preferences for deductive
formalisms frequently blind us to this
important fact, which is no less true
today than it was in 1910." By the way, note that the
phrase "formalism": here
has at least a touch of a
In the case of the sciences, negative connotation.
knowing more about, the "lower"
level, like the nature of Does it have a negative
atoms, *also* improves your connotation in general?
understanding of the "higher"
level-- we begin with chemistry FORMALIST
and use that knowledge to infer
something about atoms, and then
knowing something about atoms
then improves our understanding
of chemistry.
It is not at all clear to me
that we actually *get* anything
out of the theories of the
ultimate "foundations" of
mathematics. Once you know
something of the foundations,
can you build something you
couldn't build before?
Herbert A Simon often seems
to have a naive 1950s
optimism about, say, the
efficacy of computer But then I haven't looked at the new chapter
simulation techniques: on complexity sciences he added in 1981 for
the third edition.
"Thus we might expect simulation to be a powerful COMPLEX_SIMON
technique for deriving, from our knowledge of the
mechanisms governing the behavior of gases, a
theory of the weather and a means of weather
prediction. Indeed, as many people are aware,
attempts have been under way for some years to
apply this technique. Greatly oversimplified,
the idea is that we already know the correct
basic assumptions, the local atmospheric
equations, but we need the computer to work out
the implications of the interactions of vast
numbers of variables starting from complicated
initial conditions. This is simply an
extrapolation to the scale of modern computers of
the idea we use when we solve two simultaneous
equations by algebra." (p.15)
Weather has since become the classic example of a
system whose complexity causes it to elude much more
than short term prediction-- really, we understand
the *components* (gas molecules) extremely well,
the sheer number of them pushes us into the realm of
chaotic indeterminacy.
Simon argues for the *possibilty*
of working out rules governing
the high level behavior of a It also doesn't mean you
system, but can't really *couldn't* do the converse: work
guarantee it's achievable in out a general theory from the
advance of actually doing it. bottom up, by first understanding
the components.
"The natural laws governing relays are very well known,
while the natural laws governing neurons are known most
imperfectly. But that does not matter, for all that is
relevant for the theory is that the components have the
specified level of unreliability and be interconnected
in the specified way."
Yes, it could be that the behavior you're interested
in can be understood and predicted without regard to
the nature of the components-- but it also could be
it can't be understood of predicted *at all*, no
matter how well you understand its components.
And-- pick a different nit entirely--
In the case of computers, because they're
artificial systems, we intentionally use
different technologies to implement similar
behaviors. The programmer doesn't care if the
chips are TTL or CMOS or something else
entirely, because the circuit designer creates
a virtual entity (a "microprocessor") with a
particular external behavior.
Similarly, the Assembly language programmer
can implement an operating system that works
in a certain way, irrespective of the various
quirks of a particular microprocessor architecture.
So, if there's some independence of the behavior
of the "upper level" from the nature of it's
components, it's because it was designed in,
we implement things that way on purpose.
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