Jim Bromer wrote:
> You can't assume a priori that the diagonal argument is not relevant. 

When I say "infinite" in my proof of Solomonoff induction, I mean countably 
infinite, as in aleph-null, as in there is a 1 to 1 mapping between the set and 
N, the set of natural numbers. There are a countably infinite number of finite 
strings, or of finite programs, or of finite length descriptions of any 
particular string. For any finite length string or program or description x 
with nonzero probability, there are a countably infinite number of finite 
length strings or programs or descriptions that are longer and less likely than 
x, and a finite number of finite length strings or programs or descriptions 
that are either shorter or more likely or both than x.

Aleph-null is larger than any finite integer. This means that for any finite 
set and any countably infinite set, there is not a 1 to 1 mapping between the 
elements, and if you do map all of the elements of the finite set to elements 
of the infinite set, then there are unmapped elements of the infinite set left 
over.

Cantor's diagonalization argument proves that there are infinities larger than 
aleph-null, such as the cardinality of the set of real numbers, which we call 
uncountably infinite. But since I am not using any uncountably infinite sets, I 
don't understand your objection.

 -- Matt Mahoney, [email protected]




________________________________
From: Jim Bromer <[email protected]>
To: agi <[email protected]>
Sent: Sat, July 3, 2010 9:43:15 AM
Subject: Re: [agi] Re: Huge Progress on the Core of AGI

On Fri, Jul 2, 2010 at 6:08 PM, Matt Mahoney <[email protected]> wrote:

Jim, to address all of your points,
>
>
>Solomonoff induction claims that the probability of a string is proportional 
>to the number of programs that output the string, where each program M is 
>weighted by 2^-|M|. The probability is dominated by the shortest program 
>(Kolmogorov complexity), but it is not exactly the same. The difference is 
>small enough that we may neglect it, just as we neglect differences that 
>depend on choice of language.
 
 
The infinite number of programs that could output the infinite number of 
strings that are to be considered (for example while using Solomonoff induction 
to "predict" what string is being output) lays out the potential for the 
diagonal argument.  You can't assume a priori that the diagonal argument is not 
relevant.  I don't believe that you can prove that it isn't relevant since as 
you say, Kolmogorov Complexity is not computable, and you cannot be sure that 
you have listed all the programs that were able to output a particular string. 
This creates a situation in which the underlying logic of using Solmonoff 
induction is based on incomputable reasoning which can be shown using the 
diagonal argument.
 
This kind of criticism cannot be answered with the kinds of presumptions that 
you used to derive the conclusions that you did.  It has to be answered 
directly.  I can think of other infinity to infinity relations in which the 
potential mappings can be countably derived from the formulas or equations, but 
I have yet to see any analysis which explains why this usage can be.  Although 
you may imagine that the summation of the probabilities can be used just like 
it was an ordinary number, the unchecked usage is faulty.  In other words the 
criticism has to be considered more carefully by someone capable of dealing 
with complex mathematical problems that involve the legitimacy of claims 
between infinite to infinite mappings.
 
Jim Bromer
 
 
 
On Fri, Jul 2, 2010 at 6:08 PM, Matt Mahoney <[email protected]> wrote:

Jim, to address all of your points,
>
>
>Solomonoff induction claims that the probability of a string is proportional 
>to the number of programs that output the string, where each program M is 
>weighted by 2^-|M|. The probability is dominated by the shortest program 
>(Kolmogorov complexity), but it is not exactly the same. The difference is 
>small enough that we may neglect it, just as we neglect differences that 
>depend on choice of language.
>
>
>Here is the proof that Kolmogorov complexity is not computable. Suppose it 
>were. Then I could test the Kolmogorov complexity of strings in increasing 
>order of length (breaking ties lexicographically) and describe "the first 
>string that cannot be described in less than a million bits", contradicting 
>the fact that I just did. (Formally, I could write a program that outputs the 
>first string whose Kolmogorov complexity is at least n bits, choosing n to be 
>larger than my program).
>
>
>Here is the argument that Occam's Razor and Solomonoff distribution must be 
>true. Consider all possible probability distributions p(x) over any infinite 
>set X of possible finite strings x, i.e. any X = {x: p(x) > 0} that is 
>infinite. All such distributions must favor shorter strings over longer ones. 
>Consider any x in X. Then p(x) > 0. There can be at most a finite number (less 
>than 1/p(x)) of strings that are more likely than x, and therefore an infinite 
>number of strings which are less likely than x. Of this infinite set, only a 
>finite number (less than 2^|x|) can be shorter than x, and therefore there 
>must be an infinite number that are longer than x. So for each x we can 
>partition X into 4 subsets as follows:
>
>
>- shorter and more likely than x: finite
>- shorter and less likely than x: finite
>- longer and more likely than x: finite
>- longer and less likely than x: infinite.
>
>
>So in this sense, any distribution over the set of strings must favor shorter 
>strings over longer ones.
>
>
>
>-- Matt Mahoney, [email protected] 
>
>
>
>
>
________________________________
 From: Jim Bromer <[email protected]>
>To: agi <[email protected]>
>Sent: Fri, July 2, 2010 4:09:38 PM 
>
>
>Subject: Re: [agi] Re: Huge Progress on the Core of AGI
>
>
>
>
>
>On Fri, Jul 2, 2010 at 2:25 PM, Jim Bromer <[email protected]> wrote:  
>
>There cannot be a one to one correspondence to the representation of the 
>shortest program to produce a string and the strings that they produce.  This 
>means that if the consideration of the hypotheses were to be put into general 
>mathematical form it must include the potential of many to one relations 
>between candidate programs (or subprograms) and output strings.
> 
>But, there is also no way to determine what the "shortest" program is, since 
>there may be different programs that are the same length.  That means that 
>there is a many to one relation between programs and program "length".  So the 
>claim that you could just iterate through programs by length is false.  This 
>is the goal of algorithmic information theory not a premise of a methodology 
>that can be used.  So you have the diagonalization problem. 
> 
>A counter argument is that there are only a finite number of Turing Machine 
>programs of a given length.  However, since you guys have specifically 
>designated that this theorem applies to any construction of a Turing Machine 
>it is not clear that this counter argument can be used.  And there is still 
>the specific problem that you might want to try a program that writes a longer 
>program to output a string (or many strings).  Or you might want to write a 
>program that can be called to write longer programs on a dynamic basis.  I 
>think these cases, where you might consider a program that outputs a longer 
>program, (or another instruction string for another Turing Machine) 
>constitutes a serious problem, that at the least, deserves to be answered with 
>sound analysis.
> 
>Part of my original intuitive argument, that I formed some years ago, was that 
>without a heavy constraint on the instructions for the program, it will be 
>practically impossible to test or declare that some program is indeed the 
>shortest program.  However, I can't quite get to the point now that I can say 
>that there is definitely a diagonalization problem.
> 
>Jim Bromer
>
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