"Symbol grounding" basically means the association of linguistic tokens
(words, linguistic concepts, etc.) with nonlinguistic (e.g.
perceptual-motor)
patterns.

E.g. associating the word "apple" with a set of visual images of apples, or
associating (some sense of) the word "from" with a set of remembered
episodes illustrating
that sense of "from-ness" ...

Clearly human language learning relies to a large extent on these kinds of
associations; a question is whether a software program could tractably learn
language without such associations, by relying solely on statistical
associations within texts.  (Note the word "tractably" in the prior sentence
-- I assume that given a sufficiently large corpus, language could be
learned solely from statistical text analysis.  But if "sufficiently large"
means octillions of documents, that doesn't matter until we get access to
the Galactic Empire's online library...)

Cyc would be an example of an AGI project that is trying to get deep
language understanding and general intelligence without any kind of symbol
grounding.

-- Ben G

On 6/11/07, James Ratcliff <[EMAIL PROTECTED]> wrote:

1. Is anyone taking an approach to AGI without the use of Symbol
Grounding?
Or is that intrinsic in everyones approaches at this stage?
(short of some Neural Network approaches)

2. How do you describe Symbol Grounding for an AGI?
What do you consider the best ways to have the system get Symbol
Grounding?

James

*Joshua Fox <[EMAIL PROTECTED]>* wrote:

Josh,

Thanks for that answer on the layering of mind.


> It's not that any existing level is wrong, but there aren't enough of
them, so
> that the higher ones aren't being built on the right primitives in
current
> systems. Word-level concepts in the mind are much more elastic and
plastic
> than logic tokens.

Could I ask also that you take a stab at a psychological/sociological
question:  Why have not the leading minds of AI (considering for this
purpose only the true creative thinkers with status in the community,
however small a fraction that may be) taken a sufficiently multi-layered,
grounded  approach up to now? Isn't the need for grounding and deep-layering
obvious to the most open-minded and intelligent of researchers?

Joshua
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