The Halting Problem shows that the results of programs (programmable logic)
cannot be completely computed - for every possible program - without
running the program. (The Gödel Incompleteness Theorem shows that there
are -some- comprehendible logical problems that could not even be
theoretically resolved programmatically.)

But there are some programs that can be computationally processed so that a
system of results can be produced more quickly than actually running the
program.

The significance of this came to me after I started criticizing the
proposition that an advanced representational compression could
be sufficient to produce AGI at this time. The problem is that
representational compressions have to go through stages of decompression
and recompression in order to do any computation on the data, and given the
degree of compression that would be needed for AGI that would make the
system way too slow.

While logical computation is a simple process using binary representations
of simple logical states for each literal (logical variable), the problem
is that logical Satisfiability statements are (most familiarly)
compressions of multiple logical states. A logical statement is (typically)
a compression of a system of individual 'solutions'. So what would
be needed would be a computational method that can act efficiently on a
wide variety of logical solutions. In other words we need a compression
method which can do computations on the compressed representations without
(excessively) decompressing them for each computation. I started thinking
about this project from the view that my goal is not to make p=np but to
try to develop a methodology that might one day be more efficient than
methods that we currently use.

I started thinking that it might be possible to create compression
representations that acted from different levels of abstraction. These
levels of abstraction might be thought of as programs. I started thinking
about Turing's Halting Problem and I realized that while you cannot find a
shortcut to the completion state of every possible computer program,
you can for some kinds of programs. The results of a system that I
am imagining could be decompressed (at the end of the analytical
computational stages) to produce solutions using the levels-of-abstraction
sub-program. but the system could run through the computational steps
without actually running that sub-program. The compressed representations
would not have to be excessively decompressed in order to run a computation
on them.

I am all but certain that an example is feasible (although I do not have
one right now).

And incidentally, an advancement that shows that a compression system might
be accompanied by an effective computational method that can act on the
compressed representations without fully decompressing them might be
interesting to some people. The system does not have to beat Turing at
run-around-the-house chess or to prove Gödel wrong from under a table at a
week-long Oktoberfest or be dependent on winning a million dollars, it only
has to be interesting, incrementally improvable and salient to the study of
logic.
Jim Bromer



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AGI
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