Hi Steve,

> is the logical extension of this to the *approximate* (by dropping
selected terms) *algebraic* (which may include embedded numerical values)
solutions to systems of >*simultaneous* *non-linear* and *differential* *
equations*. Once this engine is in place, my claim is that much of AGI
should easily fall into place, and further, that many of the >present
"grand challenges" in AGI are in actuality simply presenting the problems
that surface when you try doing AGI-like things without such an engine in
place.

OK, I agree -  those equations, especially differential, are an expression
of the model for prediction/defining the "correlations" between inputs and
future inputs/outputs. In terms from my works the differences between
samples/patterns are called "correlations", these differences (and
delta-encoding) actually are defining differential equations (in a digital
way), and that's how to produce/predict following data, given samples and
the "correlation" to the future (that's a "pattern"). This can be extended
in many levels of abstraction, these are higher order
correlations/differential equations. I agree that a general algorithm for
finding those general correlations (something AGI is searching for) is like
a universal "definer" of differential equations and non-linear equations
from data, and it's what an AGI should be capable to do. The
wild non-linear equations (especially very complex ones, with raises,
falls, spikes) which are hard to represent "simply"/to compress well are
just mappings, one vector is mapped to another, because of some kind of
coincidence/repetition.

>Ben had the right idea in creating an engine like OpenCog rather than
trying to do everything with ad hoc programming. I think that Ben's error
was working at too >low a level, e.g. of handling probabilities at
particular moments in time.

I believe it's not him only, after all that's the idea of AGI, to solve
everything possible with a smooth integral framework, instead of working
ad-hoc.


*--- Todor "Tosh" Arnaudov --*
*"Twenkid Research*" -  http://research.twenkid.com
 *Self-Improving General Intelligence Conferenc*e Chair :
http://artificial-mind.blogspot.com/2012/07/news-sigi-2012-1-first-sigi-agi.html


On Fri, Aug 10, 2012 at 1:12 AM, Todor Arnaudov <[email protected]> wrote:

> Hi Steve,
>
> >There have been a number of programs written that were capable of
> manipulating algebraic formulas, and some to solve isolated equations.
> There have also been programs to solve simultaneous *linear* equations
> >via array operations. In the engine I envision, every "formula" would be
> presumed to equal zero, and hence would be an equation, despite its missing
> = sign, similar to array operator implementations to solving
> >simultaneous linear equations. Instead of operators like "addition" or
> "subtraction", there would be new operators like "union" that would solve a
> system of simultaneous NONlinear equations, etc.
>
> What are you talking about, solving equations and general algebraic
> operations algorithms are mathematically solved (for linear ones - for
> sure), we wouldn't be able to solve them by hand if it was not. One of
> the *first (some claim it's the first)* electronic computers  itself was
> designed precisely to solve linear equations with 30 unknowns (the ABC,
> Atanassoff-Berry-Computer), because the other methods were too slow for the
> needs of John Atanassoff. The computer was conceived in 1937. Vladimir
> Turchin has written algebraic programs in the 60-ies with his programming
> language REFAL. http://www.encyclopediaofmath.org/index.php/Refal
> Functional and Logical Languages in general are
> somewhat intrinsically "algebraic", unlike procedural like C, which are
> more "computational/arithmetical".
>
> The "Matrix processors", the first "SIMD-MIMD" etc. and multi-processing
> units devices started with multiplication + addition done much quickly than
> general purpose computers, because that's a critical operation for
> scientific computation, which are largely for computation of "matrices"
> including solving linear equations. With the advent of video cards for
> PCs, then the GPU, that's now in every PC's GPU with huge parallelism,
> sometimes capable of many TFLOPS.
>
> In computer vision there are such equations for example when triangulating
> a stereo image into 3D object, and calibrating a camera parameters from
> taken pictures.I've written a simple program to solve such myself as a
> student, using the same algorithm as I'd apply manually - Mathematica
> solves all kinds of algebraic expressions, AFAIK it's done also in one
> extent or another using REFAL: http://integrals.wolfram.com/index.jsp
>
>
> *--- Todor "Tosh" Arnaudov --*
> *"Twenkid Research*" -  http://research.twenkid.com
>  *Self-Improving General Intelligence Conferenc*e Chair :
> http://artificial-mind.blogspot.com/2012/07/news-sigi-2012-1-first-sigi-agi.html
>
>
>


-- 
*--- Todor "Tosh" Arnaudov ---*
*
-- Twenkid Research:*  http://research.twenkid.com

-- *Self-Improving General Intelligence Conference*:
http://artificial-mind.blogspot.com/2012/07/news-sigi-2012-1-first-sigi-agi.html

*-- Todor Arnaudov's Researches Blog**: *http://artificial-mind.blogspot.com



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