Jim,

Fair enough.

Oh, and Matt: kudos for being better at patiently explaining details than
me.

--Abram

On Mon, Jul 26, 2010 at 4:11 PM, Jim Bromer <jimbro...@gmail.com> wrote:

> Abram,
> We all have some misconceptions about this, and about related issues.  Let
> me think about this more carefully and I will answer during the next week -
> or two, (I have already reached my quota of egregious errors in this
> thread).
> Jim
>
> On Mon, Jul 26, 2010 at 2:54 PM, Abram Demski <abramdem...@gmail.com>wrote:
>
>> Jim,
>>
>> I'll argue that solomonoff probabilities are in fact like Pi, that is,
>> computable in the limit.
>>
>> I still do not understand why you think these combinations are necessary.
>> It is not necessary to make some sort of ordering of the sum to get it to
>> converge: ordering only matters for infinite sums which include negative
>> numbers. (Perhaps that's where you're getting the idea?)
>>
>> Here's my proof, rewritten from an earlier post, using the properties of
>> infinite sums of non-negative numbers.
>>
>> (preliminaries)
>>
>> Define the computation as follows: we start with a string S which we want
>> to know the Solomonoff probability of. We are given a time-limit T. We start
>> with P=0, where P is a real number with precision 2*log_4(T) or more. We use
>> some binary encoding for programs which (unlike normal programming
>> languages) does not contain syntactically invalid programs, but still will
>> (of course) contain infinite loops and so on. We run program "0" and "1" for
>> T/4 each, "00", "01", "10" and "11" for T/16 each, and in general run each
>> program of length N for floor[T/(4^N)] until T/(4^N) is less than 1. Each
>> time we run a program and the result is S, we add 1/(4^N) to P.
>>
>> (assertion)
>>
>> P converges to some value as T is increased.
>>
>> (proof)
>>
>> If every single program were to output S, then T would converge to 1/4 +
>> 1/4 + 1/16 + 1/16 + 1/16 + 1/16 + ... that is, 2*(1/(4^1)) + 4*(1/(4^2)) +
>> 8*(1/(4^3)) + ... which comes to 1/2 + 1/4 + 1/8 + 1/16 + .. i.e. 1/(2^1) +
>> 1/(2^2) + 1/(2^3) + ... ; it is well-known that this sequence converges to
>> 1. Thus 1 is an upper bound for P: it could only get that high if every
>> single program were to output S.
>>
>> 0 is a lower bound, since we start there and never subtract anything. In
>> fact, every time we add more to P, we have a new lower bound: P will never
>> go below a number once it reaches it. The sum can only increase. Infinite
>> sums with this property must either converge to a finite number, or go to
>> infinity. However, we already know that 1 is an upper bound for P; so, it
>> cannot go to infinity. Hence, it must converge.
>>
>> --Abram
>>
>>   On Mon, Jul 26, 2010 at 9:14 AM, Jim Bromer <jimbro...@gmail.com>wrote:
>>
>>>   As far as I can tell right now, my theories that Solomonoff Induction
>>> is trans-infinite were wrong.  Now that I realize that the mathematics do
>>> not support these conjectures, I have to acknowledge that I would not be
>>> able to prove or even offer a sketch of a proof of my theories.  Although I
>>> did not use rigourous mathematics while I have tried to make an assessment
>>> of the Solomonoff method, the first principle of rigourous mathematics is to
>>> acknowledge that the mathematics does not support your supposition when they
>>> don't.
>>>
>>> Solomonoff Induction isn't a mathematical theory because the desired
>>> results are not computable.  As I mentioned before, there are a great many
>>> functions that are not computable but which are useful and important because
>>> they tend toward a limit which can be seen in with a reasonable number of
>>> calculations using the methods available.  Pi is one such function.  (I am
>>> presuming that pi would require an infinite expansion which seems right.)
>>>
>>> I have explained, and I think it is a correct explanation, that there is
>>> no way that you could make an apriori computation of all possible
>>> combinations taken from infinite values.  So you could not even come up with
>>> a theoretical construct that could take account of that level of
>>> complexity.  It is true that you could come up with a theoretical
>>> computational method that could take account of any finite number of values,
>>> and that is what we are talking about when we talk about the infinite, but
>>> in this context it only points to a theoretical paradox.  Your theoretical
>>> solution could not take the final step of computing a probability for a
>>> string until it had run through the infinite combinations and this is
>>> impossible.  The same problem does not occur for pi because the function
>>> that produces it tends toward a limit.
>>>
>>> The reason I thought Solomonoff Induction was trans-infinite was because
>>> I thought it used the Bayesian notion to compute the probability using all
>>> possible programs that produced a particular substring following a given
>>> prefix.  Now I understand that the desired function is the computation of
>>> only the probability of a particular string (not all possible substrings
>>> that are identical to the string) following a given prefix.  I want to study
>>> the method a little further during the next few weeks, but I just wanted to
>>> make it clear that, as far as now understand the program, that I do not
>>> think that it is trans-infinite.
>>>
>>> Jim Bromer
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>>
>>
>> --
>> Abram Demski
>> http://lo-tho.blogspot.com/
>> http://groups.google.com/group/one-logic
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-- 
Abram Demski
http://lo-tho.blogspot.com/
http://groups.google.com/group/one-logic



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