Matt,

I agree with Ben.  Tomassello's book Constructing a Language, A Usage-Based 
Theory of Language Acquisition argues that young children develop the skill to 
discern the intentional actions of others.  Construction Grammar (CxG) is a 
simple pairing of form and meaning.  According to this theory, implemented in 
my Incremental Fluid Construction Grammar, children learn the pairings of what 
their parents say and what their parents' intentions are.  Children generalize 
(i.e. induce) patterns among the instance pairings they experience.  CxG names 
these patterns Constructions.  In my Incremental Fluid Construction Grammar 
these constructions are assembled from the input utterance word by word by the 
application of production rules against a growing feature structure in working 
memory.  To get my bootstrap dialog system going I will explicitly code as few 
of these rules as are necessary.  However I do not believe that my system 
should learn these rules from
 percepts alone.

Let's see if it works.  I hope that in some months we can debate its actual 
behavior.

-Steve
 
Stephen L. Reed 
Artificial Intelligence Researcher
http://texai.org/blog
http://texai.org
3008 Oak Crest Ave.
Austin, Texas, USA 78704
512.791.7860

----- Original Message ----
From: Benjamin Goertzel <[EMAIL PROTECTED]>
To: [email protected]
Sent: Thursday, January 10, 2008 9:14:43 PM
Subject: Re: [agi] Incremental Fluid Construction Grammar released

 On Jan 10, 2008 10:03 PM, Matt Mahoney <[EMAIL PROTECTED]> wrote:
> All this discussion of building a grammar seems to ignore the obvious  fact
> that in humans, language learning is a continuous process that does  not
> require any explicit encoding of rules.  I think either your model  should
> learn this way, or you need to explain why your model would be more  
> successful
> by taking a different route.  Explicit encoding of grammars has a  long 
> history
> of failure, so your explanation should be good.  At a minimum, the  
> explanation
> should describe how humans actually learn language and why your  method is
> better.

Matt,

If you read the paper at the top of this list

http://www.novamente.net/papers/

you will see a brief summary of the reasoning behind the approach I am
taking.  It is only 8 pages long so it should be quick to read, though
it obviously
does not explain all details in that length.

The abstract is as follows:

*****
Abstract— Current work is described wherein simplified
versions of the Novamente Cognition Engine (NCE) are being
used to control virtual agents in virtual worlds such as game
engines and Second Life.  In this context, an IRC (imitation-
reinforcement-correction) methodology is being used to teach
the agents various behaviors, including simple tricks and
communicative acts.   Here we describe how this work may
potentially be exploited and extended to yield a pathway
toward giving the NCE robust, ultimately human-level natural
language conversation capability.  The  pathway starts via
using the current system to instruct NCE-controlled agents in
semiosis and gestural communication; and then continues via
integration of a particular sort of hybrid rule-based/statistical
NLP system (which is currently partially complete) into the
NCE-based virtual agent system, in such a way as to allow
experiential adaptation of the rules underlying the NLP system,
*****

I do not think that a viable design for an AGI needs to include a  description 
of
human learning (of language or anything else).  No one understands  exactly
how the human brain works yet, but that doesn't mean we can't  potentially
have success with non-brain-emulating AGI approaches.

My favorite theorists of human language are Richard Hudson (see his  2007
book Language Networks) and Tomassello (see his book Constructing a
Language).  I actually believe my approach to language in AGI is quite
close to their ideas.  But I don't have time/space to justify this  statement in
an email.

-- Ben

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