From: pollack@dendrite.cis.ohio-state.edu (Jordan B Pollack)
Subject: Re: bboard to discuss genetic alg, connectionism, artificial life?
Originator: pollack@dendrite.cis.ohio-state.edu
Reply-To: pollack@cis.ohio-state.edu
Organization: Ohio State Computer Science
	<1992Oct4.041704.6346@CSD-NewsHost.Stanford.EDU>
	<POLLACK.92Oct5115554@dendrite.cis.ohio-state.edu>
	<1992Oct5.162554.1024@CSD-NewsHost.Stanford.EDU>
Date: Tue, 6 Oct 1992 15:41:15 GMT

In response to my call for broad definition, Matt Ginsberg writes:

>What you are proposing, I'm afraid, is that we let our funders decide
>which areas of AI should prosper (the most trendy, probably) 

What I am saying is that when AI prematurely rejects certain
approaches to its problems, (rather than co-opting them with a
percentage of our niche), they develop their own survival mechanisms,
including "funders" who do not pay attention to practising AI scientists.

>My goal is to prune early the stuff that hasn't got a chance of
>succeeding.  If I do so, hopefully what's left will eventually succeed
>in the goal of constructing an intelligent artifact. Why do you
>believe that any specific methodology must eventually become
>exhausted?

I have no such goal because artificial selection doesn't work in the
long run. Firstly, if you are incomplete in your pruning, i.e. when
you weed, then turn your back, you discover the weeds have returned 10
times stronger. Secondly, the stuff "thats left" may have a temporary
advantage of a protected niche, but when new competition arises, it
can be weak and flabby. Finally, I'm sure we agree on mechanistic
universality, so a specific universal method for acquiring knowledge
will never become "exhausted," per say, but it might slow down with
age and be overtaken by a more youthful universal method.

>Can you cite me an example from anywhere in science where this
>sort of magical progress appeared?

Funny! The more we understand, the less "magical" it appears.  The
"miracle" of life itself is, in my opinion, the only REALLY successful
machine learning system, and may be described as a non-equilibrium
liquid-phase chemical reaction, which converts energy through
computation into organized complexity.

Why call liquids a form of computation? The harder and harder it is to
come up with a purely logical theory of liquids, and the more CM and
Cray time it takes to simulate them, the more it becomes apparent that
liquids are performing lots of raw computation, in the form of
environmentally sensitive state changes with unbounded (distal)
dependencies.

Research in non-linear systems sheds light on non-grammatical theories
about how how context-sensitive complexity is generated from iterated
simple non-linearity. But meaningless syntactic complexity is easy to
generate.  Meaningful complexity, with domain knowledge, requires
selective filters, and the filters themselves are of course complex.
Interesting work on co-evolution of generators and filters include
recent work (in AI???)  by Tesauro on backgammon and Hillis on
sorting.

>We in AI have to make progress the old fashioned way.  We have to earn it.

True. But we all don't have to wear suits from Barney's :)





-- 
Jordan Pollack                            Assistant Professor
CIS Dept/OSU                              Laboratory for AI Research
2036 Neil Ave                             Email: pollack@cis.ohio-state.edu
Columbus, OH 43210                        Phone: (614)292-4890 (then * to fax)
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