From: James Rogers (jamesr@best.com)
Date: Mon Jun 24 2002 - 16:15:45 MDT
On Sun, 2002-06-23 at 11:47, Eliezer S. Yudkowsky wrote:
>
> In my experience, your instincts are correct; this doesn't apply to AI, but
> applies to everything else. Excessive complexity usually arises from a lack
> of true understanding of the problem domain, and simple systems with good
> architectures are usually far better than complex ones. Except in AI, where
> the problem is far more complex than your brain "wants" to think - in part
> because of all the complexity of thinking is invisible to you, and in part
> because usually humans just don't deal with things that complex.
This is a bizarre comment, and I am having difficulty interpreting it in
a way that makes sense. Complexity does not have a subjective
interpretation in proper engineering, and it doesn't follow that AI is
in some special category of problem. Bad engineering practice reflects
on the engineer, not the problem. Or to put it another way, regardless
of how complex the problem actually is, how do you know your perception
of the complexity is even remotely correct without going through the
rigorous theoretical normalization required to safely make that
assertion? This is a particularly relevant point if we are premising a
problem space that we are hypothesizing to be complex as such things go.
The proper engineering sequence is normalization and then intentional
denormalization to meet spec. It requires a lot of work, but any other
methodology is highly likely to result in poor design for all but the
most trivial problems.
-James Rogers
jamesr@best.com
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