Wrong agauin, As Michael Petch has already admitted of.

(His arguments refute yours quite correctly and specifically).

On Fri, Aug 21, 2009 at 13:37, Frank Berger <[email protected]> wrote:

>  What I am denoting is that the NNP "learns" the attributes of the
>>> specific roll generator you use.  And does it probably better than a
>>> human can.
>>>
>>
> This is absolute nonsens.
> Why? quite easy. Any NN I'm aware of is presented the position to evaluate
> it.
> Therefore it never sees the dice and can therefore not learn a pattern.


A state space convolutioon CAN and DOES learn attributions from a aseries of
rolls:

otherwise the network would not learn, whether held static AFTER learning or
not.

This is so close to 1st grade I wonder if people wil see it immediately.


>
>
>
>  This is interesting.  The Mersenne Twister is linear, so in principle it
>> is "easy" to learn how to predict it.  Whether a neural net will in fact
>> learn how to predict it depends on a lot of things, but it's entirely
>> believable.
>>
> The Mersenne Twister isn't cryptographic strength but fulfills quite some
> statistical tests.
> AFAIK as long as you don't need cryptogrphic strengt MT is regarded as the
> best choice.
> Therefore to train a neural net to predict something that is nearly
> undistinguish from real random
> is an absolute waste of time. Even with a simple linear congruence random
> number generator
> it's a waste of time.


When youy train the NN< it is trained.  Whether your training INTENDS to
train it in that way does not change whether or not all or a portion of that
training is in fact DOEN by the training you select for another purpose.

So your arguemnt is again specious.


>
>
>
>
>
>
>  In addition to the possibility of using physically random bits, one could
>> also try using a cryptographically secure random number generator.
>>
>>
>> http://en.wikipedia.org/wiki/Cryptographically_secure_pseudorandom_number_generator
>>
>> It would be interesting to see if training the neural nets with different
>> random number generators produces noticeably different results.
>>
> No. It wouldn't be interesting and no it wouldn't show any effect.
> Even if a RNG was heavily biased  throwin e.g. 25% 3's and even if the NN
> would see the dice the effect would even out over the large number of
> different positions presented the net during learning. And even if there was
> an effect on the 8th post point digit it would be completely overridden by
> the effect of the initial randomization of the NN


Noo, it owuld NOT even out; any experience Backgammon player will tell you
that.

For example, removing ALL threes from the rolls WIL produce a DIFERENT game
Similarly, removing 99.99%, 899.9% or 90%.

ANY bias wil change the flow of the game.  ANY game.



>
>
> Analyzing the effect of rng on NN seems to me as useful as analyzing
> conspiracy theory...


Ad hominems.  Not math, and not nackgamoon, fer sure.

> .
>
>
>
>
>
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