I am very glad that Mark posted the random seed idea. I have spent
some time trying to get better random results in different projects
but I think that reseting the random seed would have been a lot easier.
Regards,
Mark ---- (Tom McGrath)
Lazy River Software
[EMAIL PROTECTED]
iTunes Library Suite - libITS
Information and download can be found on this page:
http://www.lazyriversoftware.com/RevOne.html
On Nov 12, 2008, at 1:04 PM, Jacques Hausser wrote:
Many thanks for your two cents !
I wonder if the first name of people answering my first question is
really random : Mark, Mark and Mark...
Jacques
Le 12 nov. 2008 à 18:46, Mark Brownell a écrit :
I'm surprised that the random seed was not mentioned. Please excuse
this if someone has responded with that. I'm on digest mode.
I've solved the random RNG problem by simulating the function of
the Roulette wheel. This idea of using random bits or like some
websites do it is the clue. When Revolution starts up it sets a new
random seed and uses that same seed until the application shuts
down. If you reset the random seed for each spin, like on a
roulette wheel, then you can combine several things that must
happen before the ball lands in a single slot. You can randomize
the spin speed, the wheel speed, the track resistance, the bumper
strike positions or misses, and the slot fin strikes or misses. In
this way, by combining several random conditions you can do as well
as any accepted form of so called true randomness.
So I would stack about five different conditions that include
millions of possibilities and use that to randomize the final
outcome. I would always set a new random seed before starting.
My two cents,
another; Mark
Message: 8
Date: Tue, 11 Nov 2008 22:16:18 +0100
From: Jacques Hausser <[EMAIL PROTECTED]>
Subject: Random algorithm
Hi,
Does somebody know which algorithm is hidden behind the random
function ? Native random number generators have usually a poor
reputation, and I need trustable random numbers. I have translated
the
Mersenne twister algorithm which works OK, but slowly (47
milliseconds
for 1000 numbers against five for the random function). If the
native
function is a good one, I'll keep it...
Thanks for any hint
Jacques
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