The language model does not need interaction with the environment when the
language model is already complete which is possible for formal languages
but nearly impossible for natural language. That is the reason why formal
language need much less cost.
Yes! But the formal languages need to be efficiently extensible as well
(and ambiguity plays a large part in extensibility which then leads to . . .
. :-)
If the language must be learned then things are completely different and
you
are right that the interaction with the environment is necessary to learn
L.
How do you go from a formal language to a competent description of a messy,
ambiguous, data-deficient world? *That* is the natural language question.
What happens if I say that language extensibility is exactly analogous to
learning which is exactly analogous to internal model improvement?
But in any case there is a complete distinction between D and L. The brain
never sends entities of D to its output region but it sends entities of L.
Therefore there must be a strict separation between language model and D.
I disagree with a complete distinction between D and L. L is a very small
fraction of D translated for transmission. However, instead of arguing that
there must be a strict separation between language model and D, I would
argue that the more similar the two could be (i.e. the less translation from
D to L) the better. Analyzing L in that case could tell you more about D
than you might think (which is what Pinker and Hauser argue). It's like
looking at data to determine an underlying cause for a phenomenon. Even
noticing what does and does not vary (and what covaries) tells you a lot
about the underlying cause (D).
----- Original Message -----
From: "Dr. Matthias Heger" <[EMAIL PROTECTED]>
To: <agi@v2.listbox.com>
Sent: Sunday, October 19, 2008 3:50 PM
Subject: AW: [agi] Re: Meaning, communication and understanding
The language model does not need interaction with the environment when the
language model is already complete which is possible for formal languages
but nearly impossible for natural language. That is the reason why formal
language need much less cost.
If the language must be learned then things are completely different and
you
are right that the interaction with the environment is necessary to learn
L.
But in any case there is a complete distinction between D and L. The brain
never sends entities of D to its output region but it sends entities of L.
Therefore there must be a strict separation between language model and D.
- Matthias
Vladimir Nesov wrote
I think that this model is overly simplistic, overemphasizing an
artificial divide between domains within AI's cognition (L and D), and
externalizing communication domain from the core of AI. Both world
model and language model support interaction with environment, there
is no clear cognitive distinction between them. As a given,
interaction happens at the narrow I/O interface, and anything else is
a design decision for a specific AI (even invariability of I/O is, a
simplifying assumption that complicates semantics of time and more
radical self-improvement). Sufficiently flexible cognitive algorithm
should be able to integrate facts about any "domain", becoming able to
generate appropriate behavior in corresponding contexts.
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agi
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