The parent child relationship is not properly biased
against the positional token/structure.
To actually make this thought work would require an input
feedback loop of some sort so as to derive weights
from actual data over time in a fashion that builds
it's own patterns , which then is mated.
"Arthur T. Murray" wrote:
>> KNOWLEDGE BASE OR BUST
>> Today after a hiatus of two and a half months we resume coding
>http://mind.sourceforge.net/index.html the AI Mind in JavaScript.
> First we change the "description" meta-tag to read: "Please find
> room for this AI as mind.html on your own website so that others
> may obtain it." The idea is to let the AI spread memetically
> across the Web.
>> Our next goal is to obtain a working knowledge base (KB). That
> goal is immensely worthwhile because, once our KB works reliably,
> it will be like the http://www.cyc.com Cyc project, and we will
> be able to pack the KB full of all kinds of mundane or expert
> knowledge.
>> The source code left over from 29sep2001 still gives a transcript
> with faulty KB reasoning:
>> Human: cats eat fish
> Robot: CATS EAT FISH
> 32 28 10
>> Human: fish eat bugs
> Robot: FISH EAT BUGS
> 20 41 10
>> Human: bugs eat dirt
> Robot: BUGS EAT DIRT
> 20 41 10
>> Human: cats eat
> Robot: CATS EAT BUGS
> 10 41 10
>> The AI gives the wrong answer in the fourth exchange because the
> concept of "bugs" has retained too high an activation.
>> I ran the above four exchanges through only in Transcript mode so
> that I could inspect the logic of the reasoning of the AI. Then I
> went back and used the same inputs in Troubleshoot mode. I
> obtained the same results, but this time each line of output had
> the concept-activation numbers interspersed among the English
> words of the output. I look at those three-number sets and I
> think, gee, maybe I should have written the numbers down beneath
> each of the four lines of output that I transcribed above. Then
> I realize that I can run the same inputs all over again and write
> down the numbers in red. Here goes. See above for the results.
>> Well, what do you know? The output activation-levels were the
> same (20, 41, 10) in the middle two exchanges but different in
> the first (32, 28, 10) and in the fourth (10, 41, 10), where I
> entered only a partial sentence of "cats eat" in order to see
> what the AI knew about cats.
>> Now, I myself as the programmer and theoretician Arthur T. Murray
> realize how complex the deep mental processing is behind these AI
> Mind outputs, but I do not immediately realize exactly what to do
> in order to correct the problems and to perfect the knowledge
> base (KB). I only know some general methods of tracking down and
> analysing exactly what is happening in the artificial mind at
> each stage in the process of thinking. The work is daunting, and
> I think, am I up to this? Yes, I have to be, because nobody else
> is going to understand the work that has gone before or is going
> to have faith in the future of this project. When I finally have
> a knowledge base that works reliably, then people will make the
> effort to understand the AI and to develop it further.
--
--=<> Dr. Clue (A.K.A. Ian A. Storms) <>=--
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--=<[]>=- http://www.drclue.net/F1.cgi/HTML/HTML.html (My famous
HTML/CGI guide.)
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