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From: Huang on 13 Jun 2010 23:29
On Jun 13, 5:49 pm, Huang <huangxienc...(a)yahoo.com> wrote:
> OK - so a couple days ago I tried to model motion using some simple
> parametric methods, but instead of using mathematics - tried to use
> existential indeterminacy.
>
> I believe that my solution was either incomplete - or most likely
> wrong. But was a decent attempt.
>
> I have found a better way to approach this problem, and will explain
> it here.
>
> Elsewhere, I stated that "Every probabilistic problem can be restated
> in terms of existential indeterminacy and conservation of existential
> potential."
>
> So - perhaps the easiest way to write this model would be to start
> with the probabilistic model and then convert that into conjecture.
> That might be much easier, and I'll try to put together a
> probabilistic parametrization in vector notation of rectilinear
> motion, once Ive got that the random variable are like sitting ducks
> and the whole model can be reworded into a conjectural model very
> easily.
>
> After doing a few of these, formulating conjectural models from
> scratch might be easier.


So here's the plan.

Ordinarily parametric equations can be used to model motion something
like this, using a vector valued function, say

f = < a, b, t > where t = [ 0, 10 ]

and it's pretty easy to imagine something moving from < a, b, 0 > to <
a, b, 10 > as t goes from 0 to 10.

Simple.

So, instead of t, we substitute a random variable which has the same
expected value as t in the above equation.

For example

f = < a, b, T > where T is a random variable with parametrized
outcome space { T | t-1, t+1 } , t = [ 0, 1]

Because of this parametrization, the expected value ot T is always
just the same as t.

Now then, this may seem like a _trivial_ procedure, and in a strict
sense it is, (but informally it is nontrivial because it will
faciltate the transformation which we know is not orthodox
mathematics, but more an artifact of philosophy at this point).


Since we now have the vector valued function describing rectilinear
motion, and we wrote it in probabilistic form, we can easily focus
attention on the random variable and reword the whole thing in terms
of existential indeterminacy and conservation of existential
potential.

Do that with a few different examples and things will start making
more sense, and writing conjectural models should become very natural
eventually.








From: Huang on 14 Jun 2010 11:14
On Jun 13, 10:29 pm, Huang <huangxienc...(a)yahoo.com> wrote:
> On Jun 13, 5:49 pm, Huang <huangxienc...(a)yahoo.com> wrote:
>
>
>
>
>
> > OK - so a couple days ago I tried to model motion using some simple
> > parametric methods, but instead of using mathematics - tried to use
> > existential indeterminacy.
>
> > I believe that my solution was either incomplete - or most likely
> > wrong. But was a decent attempt.
>
> > I have found a better way to approach this problem, and will explain
> > it here.
>
> > Elsewhere, I stated that "Every probabilistic problem can be restated
> > in terms of existential indeterminacy and conservation of existential
> > potential."
>
> > So - perhaps the easiest way to write this model would be to start
> > with the probabilistic model and then convert that into conjecture.
> > That might be much easier, and I'll try to put together a
> > probabilistic parametrization in vector notation of rectilinear
> > motion, once Ive got that the random variable are like sitting ducks
> > and the whole model can be reworded into a conjectural model very
> > easily.
>
> > After doing a few of these, formulating conjectural models from
> > scratch might be easier.
>
> So here's the plan.
>
> Ordinarily parametric equations can be used to model motion something
> like this, using a vector valued function, say
>
> f = < a, b, t > where t = [ 0, 10 ]
>
> and it's pretty easy to imagine something moving from < a, b, 0 > to <
> a, b, 10 > as t goes from 0 to 10.
>
> Simple.
>
> So, instead of t, we substitute a random variable which has the same
> expected value as t in the above equation.
>
> For example
>
> f = < a, b, T > where T is a random variable with parametrized
> outcome space { T | t-1, t+1 } , t = [ 0, 1]
>
> Because of this parametrization, the expected value ot T is always
> just the same as t.
>
> Now then, this may seem like a _trivial_ procedure, and in a strict
> sense it is, (but informally it is nontrivial because it will
> faciltate the transformation which we know is not orthodox
> mathematics, but more an artifact of philosophy at this point).
>
> Since we now have the vector valued function describing rectilinear
> motion, and we wrote it in probabilistic form, we can easily focus
> attention on the random variable and reword the whole thing in terms
> of existential indeterminacy and conservation of existential
> potential.
>
> Do that with a few different examples and things will start making
> more sense, and writing conjectural models should become very natural
> eventually.- Hide quoted text -
>
> - Show quoted text -


One very interesting thing about this approach is that ANY random
variable will work, as long as the expected value of T remains the
same for whatever parametrization you choose to use.

Many readers will immediately notice that this property has some eerie
similarities to standard QM conventions. I do not believe that this is
in any way an accident.


The next step ion this derivation would be to replace the random
variable with something based on existential indeterminacy.

So, instead of the random variable { T | t-1, t+1 } , t = [ 0, 1] ,

we use the convention that the interval [ t-1, t+1 ] is existentially
indeterminate, and the potential to exist is uniformly distributed (on
this interval) and is everywhere 1/2. The expected value of this
interval is simply t.

Now, as t goes from 0 to 10, you still have the same exact solution as
if you were doing mathematics, but again I must insist that this is
certainly not orthodox mathematics by any stretch of the imagination.
Instead of modelling locations in motion through R3 (as in standard
vector calculus) you are actually bending space, and the item of
interest which moves from <0,0,0> to <0,0,10> is in fact a deformation
which is in transit from one region to another.


From: Huang on 14 Jun 2010 13:59
Uncle Al can always be counted on for his wisdom and insightful
feedback.

Gloves are OFF - Panties are ON - lets go Al.......you and me. Like
men. Show me where you see the error without all the rutabegas and
zeroK Patgonian coughing weasels.

Bring it.
From: Huang on 16 Jun 2010 21:44


Oh come all ye cowards, joyful & triumphant,
O come ye, oh come ye,
And collect - one - asswhupping
From: Huang on 18 Jun 2010 08:00
Thanks for all the great feedback. Clearly Im right and nobody can
argue against any of the silly things I say.
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