As I said, this idea came to me because I was thinking of a concise
generator to produce an immensity of different variations of a typological
character.  I really haven't figured out how difficult it would be to
create an algorithm generator, I have only been able to consider very
simple models.

One current theory in AI/AGI is that animals have many different (simple
algorithm-like) ways to react to a variety of narrow kinds of information.
For instance you will have an automatic reaction if something moves
unexpectedly from behind you if it is extremely close to your head (close
to one of your eyes). It is believed that there may be a fairly primitive
mental 'mechanism' to react to that sort of thing.  Perhaps higher
intelligence can be explained by the creation of specialized
algorithms that can react to learned kinds of information.  (I don't know
what this theory is called).  I am wondering if a system of algorithm
generators might be used to develop individual algorithms as needed.  If
feasible, this might be an economical way to create specialized algorithms
as needed without having to supply an overly extensive set of simple
algorithms that might not be used.

Also, since the parameters to the algorithm generators would be the method
by which different algorithms were generated (when the program thought that
it should try them) then it might be possible to for the program to make
educated guesses about the kind of algorithm that might be needed for a
special class of problems based on characteristics of the problem that can
be related to the parameters of previously generated algorithms.  This is a
nice theory except that there is of course a complication.  Effects might
not show up until you require a more sophisticated (or a less
sophisticated) level for an algorithm (for the generator parameters). All I
can think of is a simplistic example.  If you are mapping a curved line
vector onto a low resolution image buffer (like a display buffer), certain
details of the vector might not show up.  There is no reason that a
computer program would guess that the detail is being lost because the
image buffer is too low resolution.  On the other hand, if the program
noticed in one case that a detail all of a sudden became apparent when the
image buffer was set to a higher resolution, then it could learn
that higher resolution could bring out more detail on certain kinds of
image objects.  One possible advantage to this is that by using the
generator theory this sort of thing might be better systematized and hence
be more sensitive to formal techniques.
Jim Bromer

On Fri, Feb 8, 2013 at 11:56 AM, Piaget Modeler
<[email protected]>wrote:

>  What kinds of data objects are analyzed and what does analysis imply?
>
> If the algorithms are not solutions to gaps or impediments then what
> purpose do they serve?
>
> Kindly explain.
>
> ~PM
>
> ------------------------------
> Date: Fri, 8 Feb 2013 11:33:10 -0500
> Subject: Re: [agi] Could Algorithm Generators be a Feasible and Effective
> AGI Method?
> From: [email protected]
> To: [email protected]
>
>
> On Fri, Feb 8, 2013 at 10:38 AM, Ben Goertzel <[email protected]> wrote:
>
> "Automated program learning" is a branch of AI that seems close to what
> you have in mind...
> This is what the MOSES component of OpenCog attempts to do, though it's
> currently only really effective at learning simple sorts of programs...
> -- Ben G
>
>
> I described a very narrow type of programming object.  An Algorithm
> Generator.  Because I was able to use such colloquial terms it is something
> that almost everyone involved with programming should be able
> to understand.  Any AGI program would have to be capable of doing some
> automated program learning.  The question I was trying to explore was
> whether or not an explicit system of algorithm generators would be useful
> and how they might be used.  One might argue that any AGI program that was
> able to learn would effectively be creating (or generating) algorithms.
> What I am talking about is the question of designing mechanisms that
> explicitly generate kinds of algorithms. The algorithms that I have in mind
> are not solution algorithms (per se) but analytical algorithms (including
> algorithms that analyze data objects by making modifications).
> Jim Bromer
>
>
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