From: Richard Loosemore (rpwl@lightlink.com)
Date: Thu Oct 27 2005 - 07:58:43 MDT
This reply is primarily directed at HC and Ben Goertzel, who have given
two of the most insightful responses to what I wrote.
I won't quote your specific posts back at you, because I am trying not
to pollute the discussion with too many n-th order quotes. Instead, I
have read what you say and I will try to reply to the spirit of it.
There are a couple of subtle traps that we are falling into
sometimes when we talk about the relevance of "complex systems" to AGI
design. The second brings us right to the heart of the issue; the first
is easier, so I'll deal with that first.
The first trap is to think that I am advocating something at the
level of using specific mathematics, or known CAS systems, or accepted
CAS theories (such as they are) to be the new basis of AGI research.
Not at all: I am merely taking a fairly simple result, applying it to
cognitive systems, and coming to a conclusion about strategy. Then I'm
outa there: bye bye Santa Fe, back to work.
The second trap is much harder to state, but I'll try. It involves a
distinction between three things that I might be saying, only one of
which is true:
(1) Am I saying that the thinking and reasoning mechanisms (the ones
to be found in an adult system) are acting as a complex system on a
moment by moment basis? In other words, if we could look at the local,
low-level functioning of those mechanisms would we find a complex
systems disconnect between that level and (global) thinking and
reasoning behavior? NO! I am not saying that. I think this is
possible, but that is not my claim at the moment: Iam neutral about
this issue.
(2) Am I saying .... exactly ditto, but about the learning
mechanisms (the things that build new concepts as a result of
experience)? If we looked at the concept-building mechanisms, would we
find that we could not relate local to global? Again: NO! I am not
saying that; I am neutral about that also.
(3) What I am trying to talk about is the way that the learning
mechanisms interact with a real world environment over the course of the
system's lifetime learning, generating all the knowledge that the
system has as an adult. This is a long-term process, and the outcome,
the end result of this process is going to be governed by the cumulative
result of some very CAS-like mechanisms (the learning mechanisms)
interacting with the world. Here is where I find the trouble. This
process, considered as a system, contains at least the possibility of a
complex-systems-like disconnect between local mechanisms (the learning
mechanisms proper) and global behavior (the knowledge generated by the
mechanisms, by the time system gets to be an adult). It is not a matter
of moment by moment disconnect, it is a lifetime disconnect.
To illustrate with an example of what might happen: you could insert
your chosen learning mechanisms, let them interact with the world, and
then be surprised at the end of the day to find that, say, the system
just never managed to get certain kinds of abstraction; and when you
tried to figure out why this was happening, there might be nothing
local that you could put your finger on. You would simply be getting
something wrong at the end of the process, but because it was a result
of a long-term interaction (i.e. a complex system effect), you might not
be able to attack it directly.
Now, in one sense all I want to do is get people to discuss this latter
possibility. Just the possibility! I want someone to acknowledge that
this might turn out to the way things happen. We might not have
seriously run up against the problem yet, because enobody has subjected
their AGI model to the test of getting it to build almost all of its
knowledge using just the combination of learning mechanisms and messy
real-world experience. Is that not also agreed? That no one has really
done an end-to-end test of a real, non-toy, general knowledge-
acquisition mechanism yet?
And if this is true (that nobody has done such a test yet), is it not
true that if my hypothesis is true, the only way we might to start to
really notice the effect is after we had done a few long-term learning
runs and noticed that the learning mechanisms were simply not working?
You might say: why expect trouble when we have no reason to believe
that there will be trouble. My response has been: if the learning
mechanisms have the characteristics we generally think of them as
having, and if as a result they look like they will display the usual
complex systems disconnect between local and global, the experience of
the complex systems community is that it would be truly astonishing if
we did not have trouble.
Finally, I am using this argument as a reason to adopt a new research
*paradigm* (exemplified by my suggested development environment and
methodology), not a particular *model of cognition*. I was very clear
about this, but a number of people have persistently and viciously
slammed my words because they say the model [sic] I have proposed is
stupidly vague. There was never any such model.
I think this is the clearest I have managed to state the argument.
I might add that anyone who advances a thesis in this kind of forum is
always caught between a rock and a hard place: if I am brief, my
wording is so concise that it lends itself nicely to misinterpretation
by people who take one paragraph at a time and criticise out of context;
but if I give a long, detailed account I am accused of being
long-winded. Damned if I do, damned if I don't.
Richard Loosemore.
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