Good pseudo random number generator in 8080??

[Patrick Jackson]

I'm trying to make a 2048 game in 8080 assembly, and I'm stuck on a bit where I want to place a random tile of '2' every time you hit a key.

Right now, it searches through a list of 16 numbers. If it is a ZERO, then its an open space and I can place a 1 there ('2' in the lookup table). If not a 0, then there's something there. If so, increment your random number (counter incremented by waiting for a user to hit a key) and try again.

Right now, the code isn't a game but every time you hit a key ('q' quits) it will choose a random tile and place a 2. But as the board slowly fills up and less tiles are available, the game reaches a state where the remaining handful of tiles are impossible to reach given 1) your random seed and 2) the algorithm I use to increment the seed pseudorandomly. How can I fix this?

Code (simple cp/m asm/load will build it):

https://pastebin.com/pYE1mAgD

[John Galt]

since the placement is based on a keypress. what you can do is run a counter around the keypress, then the seed will depend on when the key is pressed, each time will be a little different.

many original random generators revolved around noise in the ram on start up. but everything kind of resets itself to a known state and it makes randomness not so random.

what i did in a dice program i wrote was when the program loads it gives you a little blurb and waits for a keypress. the idea was distract you a little so you take a little time to hit the key that generates the first random seed and starts the dice program.

then i added a second seed when you re-roll the dice together with the first seed. so you get decent randomization.

all that bit shifting and grabbing a piece of memory or a sector from a disk ends up being not so random and usual repeatable.

In machines where you have a Real time clock then you would take the time down to the 1/60th of a second and generate the seed from that.

[Mark Rosenthal]

I don't think it's about the generator.  I think it's about selecting from the remaining population, regardless how small it is.  So if the remaining population  is 2, The only possible results are 1 or 2.

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[Patrick Jackson]

I solved it (shelved the problem of creating a real twister algorithm) by just "if the random number won't work, increment it until it will"