A close-up look at the cryptic RNG
Thanks to everyone who contacted our offices to inquire about random number generators, a topic that I had planned to address last week.
The truth is random number generators, which supposedly control the outcome of all gaming machines – slots, poker, keno, etc. – is a cryptic subject, made so because of the convergence of two other cryptic topics, computer technology and higher mathematics (neither of which is my strong suit).
Using information from experts in the field, the machine’s random number generator or RNG is contained in a computer chip that is constantly generating a string of numbers at a predetermined "clock speed."
When a player hits the spin button on a slot machine, or the deal button on a poker machine or the start button on a keno machine, the RNG sends out a number or series of numbers used to determine the outcome of the game.
According to one source, most machines in a casino use an RNG that then cycles 4.3 billion numbers. Theoretically, this satisfies most regulators’ requirement that the outcome of a game must be random.
In Nevada, gaming regulations require that the selection process to determine the outcome of a game must be "random," which according to Regulation 14.040, means the process "must meet 95 percent confidence limits using a standard chi-squared test for goodness of fit."
Admittedly, that’s a mouthful, but here’s my best shot at an explanation, based on interviews with geeky engineers and math wizards. The standard chi-squared test is also known as the Pearson test, which is a mathematical process that determines whether the frequency distribution of certain events observed in a sample is consistent with its theoretical distribution.
The "goodness of fit" requirement establishes whether the observed frequency distribution varies from the theoretical distribution.
The simplest example would be determining whether an ordinary six-sided die is fair, that is, all six numbers have an equal chance of turning up.
It becomes more complex with gaming machines, which typically have thousands of outcomes, whose probabilities must all add up to 100 percent.
Incidentally, those probabilities for games such as video poker and video keno, must match the same probabilities as in live games. That requirement is also contained in gaming Regulation 14.040.
As you can see, even the Gaming Control Board’s requirement of randomness is qualified; that is, it must be random, but only to a certain extent.
Just how much wiggle room that leaves manufacturers is unclear. Especially when dealing with high-tech, computerized devices that can be programmed to do virtually anything.
Getting to the operation of the RNG, experts have told me that random number generators are more accurately described as "virtual" or "pseudo" random number generators.
The explanation is that the RNG "algorithms use deterministic functions." Now we’re really getting cryptic!
What this means, according to a math expert, is that the entire cycle of numbers isn’t necessarily used to determine the outcome of every play.
Instead, only a portion of the cycle is used. Given the large number of iterations, this is sufficient to satisfy most requirements of randomness.
The entire cycle of numbers is used, however, at various times during the playing of a game, as well as at the outset or initiation of play.
I emphasize that last point because it could be intrinsic to my methodology of play, which calls for frequent "re-setting" of the keno machine. That is, cashing out and starting over.
As I’ve pointed out numerous times before, most of my significant payoffs or jackpots have come within just a handful of plays following the re-setting of the machine.
Perhaps this notion of "re-seeding" the random number generator could hold the key to why that might make a difference.
In any case, hopefully these explanations of how RNG’s work shed some light on what’s happening when we play the electronic games we enjoy so much.
Question? Comment? E-mail me at: LJ Zahm