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Notes Made On Dr. D's Eqtns 1.1, 1.2, To 1.3

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Posted by Alan on August 13, 2002 10:58:53 UTC

Looking at Dr. Dick's equations 1.1 and 1.2; and his discussion leading to equation 1.3:

As the added unknown data delivers uniqueness, I call it "name" for each adding of it.


Case (a): (data, data, data,, name1) + name 2, - a name

The rule gives (data, data, data, so the -name is one of the two names so this missing number is reasonably identified

Or case (b):

(data, data, (missing data),, name1, name2) + data, - data

As the rule gives all the data; and the two names stand out due to their uniqueness; the missing data is identified by the rule. I think. (?)

(Implicitely he made two other rules: name 1, and name 2.)

Pattern rule = rule of (data, data, data,, name1, name2) - a data or a name
= 0.


So no rule for the left-over as it is either a name or just the left-over data from the rule.

That is, the pattern rule is: no rule, as it is defined? (effectively one may claim there is a pattern rule: the rule of defining the names as UNIQUELY identifying unknown data additions.)

The pattern rule is: stream of data + 1 remaining piece of data. So any function will fit under the pattern rule.

Time: subset of set.
Probability of observing a given set of data as a function of time, as a function of a subset of a set of views?

Simple probability: several of these things

thing: (data, data, data,, name1, name2) - a name or a data

give several left-overs (names and/or data).

Probability of seeing a left-over per subset of the data?

Note: probability is a myth. The statement about "any attempt to find structure beyond" whatever, seems to be saying much the same.

Although the probability of seeing a data, a left-over per (data, data) per (data, data, data, can be calculated as a ratio?

Draw three circles (sets) each can be any size: one of these per another per the other: can calculate probability of finding that? Reminiscent of an idea about gravity as the attraction of two sets within a third.

Algorithm depends on data received to date?

Depends on the sum of histories (possible subsets of the present subset).

Method of determining it must be independent of subsetting (of time)?

So the algorithm determines the arrangement of the subsets within the current subset?

Like: how you got what you got now: any rule specifies a particular ordering of all possible paths to now?

Possible paths: alternative arrangements of subsets.

Interested in algorithms that give probability of getting a particular sequence of subsets out of all possible sequences of subsets.

(Roger Penrose's description of Schrodinger's equation looks like the algorithm-free backbone of this).

Remove constraints imposed by the data itself (blatantly QED is the underlying framework!)

Need remove: probability of getting ANY sequence of subsets from all possible sequences.

G arrow on top (x arrow on top), t) means

Rule for sequencing the data

Partially differentiate a sequence of subsets from all possible sequences.

I think I follow Dr. Dick's method to equation 1.3; what he does soon after that, why a differential volume is involved, is intuitively obvious.

It is consistent with the breakthrough made by carefully analysing his "Egyptian scenario" from Counterbalance.


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