On 2/19/08, Ben Goertzel <[EMAIL PROTECTED]> wrote:
> If we need a KB orders of magnitude larger to make that approach work,
> doesn't that mean we should use another approach?

But do you agree that a KB orders of magnitude larger is required for all
AGI, regardless of *how* the knowledge is acquired?  The debate is on how to
acquire the knowledge.


> Like, er, embodied learning or NL information extraction / conversation
...
> which have the potential to allow rules to be learned implicitly from
> experience rather than explicitly via human hard-coding...

Let me list all the ways of AGI knowledge acquisition:

A)  manual encoding in logical form
B)  manual teaching in NL and pictures
C)  learning in virtual reality (eg Second Life)
D)  embodied learning (eg computer vision)
E)  inductive learning / extraction from existing texts

I'm originally proposing A, but I'm also considering B, as Bob suggests.

C is not very viable as of now.  The physics in Second Life is simply not
*rich* enough.  SL is mainly a space for humans to socialize, so the physics
will not get much richer in the near future -- is anyone interested in
emulating cigarette smoke in SL?

D is hard.  I think I know how to do it, but it'd require $$$.

E is also hard, but you seem to be *unaware* of its difficulty.  In fact,
the problem with E is the same as that with AIXI -- the thoery is elegant,
but the actual learning would take forever.  Can you explain, in broad
terms, how the AGI is to know that water runs downhill instead of up, and
that the moon is not blue, but a greyish color?


> It just doesn't seem a pragmatically feasible approach, setting aside
> all my doubts about the AI viability of it (i.e., I'm not so sure that
even
> if you spent a billion dollars on hand-coding of rules, this would be
> all that helpful for AGI, in the absence of a learning engine radically
> different in nature from typical logical reasoning engines...)


The KB can be used in conjunction with any learning algorithm you have.  In
fact, all A-E can be used together to build the KB.  You seem to think that
method E is so superior that you don't need other sources of knowledge, but
the problem is the efficiency of the learning algorithm.

YKY

-------------------------------------------
agi
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