On Tue, Sep 30, 2008 at 6:43 AM, Ben Goertzel [EMAIL PROTECTED] wrote:
We are talking about 2 things:
1. Using an ad hoc parser to translate NL to logic
2. Using an AGI to parse NL
I'm not sure what you mean by parse in step 2
Sorry, to put it more accurately:
#1 is using an ad hoc NLP
On Tue, Sep 30, 2008 at 12:50 PM, Linas Vepstas [EMAIL PROTECTED] wrote:
I'm planning to make the project opensource, but I want to have a web
site that keeps a record of contributors' contributions. So that's
taking some extra time.
Most wiki's automatically keep tracl of who made
what
On Tuesday 30 September 2008, YKY (Yan King Yin) wrote:
Yeah, and I'm designing a voting system of virtual credits for
working collaboratively on the project...
Write a plugin to cvs, svn, git, or some other.
- Bryan
http://heybryan.org/
Engineers:
On Tue, Sep 30, 2008 at 2:58 AM, YKY (Yan King Yin)
[EMAIL PROTECTED] wrote:
On Tue, Sep 30, 2008 at 6:43 AM, Ben Goertzel [EMAIL PROTECTED] wrote:
We are talking about 2 things:
1. Using an ad hoc parser to translate NL to logic
2. Using an AGI to parse NL
I'm not sure what you
Markov chains are one way of doing the math for spreading activation, but
e.g.
neural nets are another...
On Tue, Sep 30, 2008 at 1:23 AM, Linas Vepstas [EMAIL PROTECTED]wrote:
2008/9/29 Ben Goertzel [EMAIL PROTECTED]:
Stephen,
Yes, I think your spreading-activation approach makes sense
Hi Ben,
If Richard Loosemore is half-right, how is he half-wrong?
Terren
--- On Mon, 9/29/08, Ben Goertzel [EMAIL PROTECTED] wrote:
From: Ben Goertzel [EMAIL PROTECTED]
Subject: Re: [agi] Dangerous Knowledge
To: agi@v2.listbox.com
Date: Monday, September 29, 2008, 6:50 PM
I mean that a
I don't want to recapitulate that whole long tedious thread again!!
However, a brief summary of my response to Loosemore's arguments is here:
http://opencog.org/wiki/OpenCogPrime:FAQ#What_about_the_.22Complex_Systems_Problem.3F.22
(that FAQ is very incomplete which is why it hasn't been
Ben: the reason AGI is so hard has to do with Santa Fe Institute style
complexity ...
Intelligence is not fundamentally grounded in any particular mechanism but
rather in emergent structures
and dynamics that arise in certain complex systems coupled with their
environments
Characterizing what
On Tue, Sep 30, 2008 at 12:45 PM, Mike Tintner [EMAIL PROTECTED]wrote:
Ben: the reason AGI is so hard has to do with Santa Fe Institute style
complexity ...
Intelligence is not fundamentally grounded in any particular mechanism but
rather in emergent structures
and dynamics that arise in
Right, was just looking for exactly that kind of summary, not to rehash
anything! Thanks.
Terren
--- On Tue, 9/30/08, Ben Goertzel [EMAIL PROTECTED] wrote:
From: Ben Goertzel [EMAIL PROTECTED]
Subject: Re: [agi] Dangerous Knowledge
To: agi@v2.listbox.com
Date: Tuesday, September 30, 2008,
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
On Tue, Sep 30, 2008 at 2:08 PM, Jim Bromer [EMAIL PROTECTED] wrote:
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
On Tue, Sep 30, 2008 at 2:43 PM, Lukasz Stafiniak [EMAIL PROTECTED]wrote:
On Tue, Sep 30, 2008 at 3:38 PM, Ben Goertzel [EMAIL PROTECTED] wrote:
Markov chains are one way of doing the math for spreading activation, but
e.g.
neural nets are another...
But these are related things,
And if you look at your brief answer para, you will find that while you
talk of mappings and constraints, (which are not necessarily AGI at all),
you make no mention in any form of how complexity applies to the crossing of
hitherto unconnected domains [or matrices, frames etc], which, of
Ben: 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
It doesn't have any application...
My proof has two steps
1)
Hutter's paper
The Fastest and Shortest Algorithm for All Well-Defined Problems
http://www.hutter1.net/ai/pfastprg.htm
2)
I can simulate Hutter's algorithm (or *any* algorithm)
using an attractor neural net, e.g. via Mikhail Zak's
Can't resist, Ben..
it is provable that complex systems methods can solve **any** analogy problem,
given appropriate data
Please indicate how your proof applies to the problem of developing an AGI
machine. (I'll allow you to specify as much appropriate data as you like -
any data, of
Ben,
Well, funny perhaps to some. But nothing to do with AGI - which has nothing to
with well-defined problems.
The one algorithm or rule that can be counted on here is that AGI-ers won't
deal with the problem of AGI - how to cross domains (in ill-defined,
ill-structured problems). Applies
On Tue, Sep 30, 2008 at 4:18 PM, Mike Tintner [EMAIL PROTECTED]wrote:
Ben,
Well, funny perhaps to some. But nothing to do with AGI - which has
nothing to with well-defined problems.
I wonder if you are misunderstanding his use of terminology.
How about the problem of gathering as much
Ben,
I must assume you are being genuine here - and don't perceive that you have not
at any point illustrated how complexity might lead to the solution of any
given general (domain-crossing) problem of AGI.
Your OpenCog design also does not illustrate how it is to solve problems - how
it
On Wed, Oct 1, 2008 at 8:03 AM, Mike Tintner [EMAIL PROTECTED] wrote:
Your OpenCog design also does not illustrate how it is to solve problems -
how it is, for example, to solve the problems of concept, especially
speculative concept,, formation.
You have already provided one very suitable example of a general AGI
problem - how is your pet having learnt one domain - to play fetch, - to
use that knowledge to cross into another domain - to learn/discover the
game of hide-and-seek.? But I have repeatedly asked you to give me your
Without trying to be pejorative at all, it seems that the only real way for
me to address a lot of the questions being asked here would be to write a
sort of OpenCogPrime for Dummies
[ ... note that the ... for Dummies books are not actually written for
dumb people, they just assume little
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