From: "Ben Goertzel" <[EMAIL PROTECTED]>
To give a brief answer to one of your questions: analogy is
mathematically a matter of finding mappings that match certain
constraints.   The traditional AI approach to this would be to search
the constrained space of mappings using some search heuristic.  A
complex systems approach is to embed the constraints into a dynamical
system and let the dynamical system evolve into a configuration that
embodies a mapping matching the constraints.  Based on this, it is
provable that complex systems methods can solve **any** analogy
problem, given appropriate data, and using for example asymmetric
Hopfield nets (as described in Amit's book on Attractor Neural
Networks back in the 80's).  Whether they are the most
resource-efficient way to solve such problems is another issue.
OpenCog and the NCE seek to hybridize complex-systems methods with
probabilistic-logic methods, thus alienating almost everybody ;=>
-- Ben G
--------------------------

The problem is that you are still missing what should be the main
focus of your efforts.  It's not whether or not your program does good
statistical models, or uses probability nets, or hybrid technology of
some sort, or that you have solved some mystery to analogy that was
not yet understood.

An effective program has to be able to learn how to structure its
interrelated and interactive knowledge effectively according to both
the meaning of realtively sophisticated linguistic (or linguistic like
communication) and to its own experience with other less sophisticated
data experiences (like sensory input of various kinds.)

The most important thing that is missing is the answer to the
question: how does the program learn about ideological structure?  If
it weren't for ambiguity (in all of its various forms) then this
knowledge would be easy for a programmer to acquire through gradual
experience.  But sophisticated input like language and making sense of
less sophisticated input, like simple sensory input, is highly
ambiguous and confusing to the AI programmer.

It is as if you are revving up the engine and trying to show off by
the roar of your engine, the flames and smoke shooting out the
exhaust, and the squeals and smoke of your tires burning, but then
that is all there is to it.  You will just be spinning your wheels
until you deal with the problem of ideological structure in the
complexity of highly ambiguous content.

So far, it seems like very few people have any idea what I am talking
about, because they almost never mention the problem as I see it.
Very few people have actually responded intelligibly to this kind of
criticism, and for those who do, their answer is usually limited to
explaining that this is what we are all trying to get at, or that this
was done in the old days, and then dropping it.  So I will understand
if you don't reply to this.

Jim Bromer


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agi
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