[Haskell-cafe] better way to do this?

[Ryan Ingram]

And, to go further, once you embrace "determinism" in your randomness, you
can do all sorts of really cool things.

>From the perspective of a games programmer:

You can run the same simulation code on two different network nodes, and
reliably get the same result, allowing you to just transfer user inputs
between the nodes instead of game state.  This has applications in reducing
latency as well, as you only need to transfer the input one way across the
network.

You can save off the user inputs and initial into a tiny "replay" buffer,
allowing you to re-run the game from the beginning without much memory
cost.  This is not only a cool end-user feature, but it aids *tremendously*
in debugging.  When something goes wrong, you can always just rewind as many
times as you want while you narrow down the cause of the problem.

However, we always had problems with determinism failures, where somebody
would use the wrong random-number generator, or forget that they aren't
allowed to have the simulation depend on something that came from the
graphics RNG.  In Haskell you can encode the purity of the simulation into
its type and it won't break!

  -- ryan

On Sun, Oct 4, 2009 at 6:20 AM, Duncan Coutts
<duncan.coutts at googlemail.com>wrote:

> On Sun, 2009-10-04 at 05:11 -0700, Michael Mossey wrote:
> > Duncan Coutts wrote:
>
> > > Others have already answered but I'd like to suggest that you avoid
> > > using IO here. There's no need for this to be impure.
>
> > Can you point me to a tutorial that covers the basics of randomness in
> > Hasell? I find it very confusing.
>
>
> http://en.wikibooks.org/wiki/Haskell/Hierarchical_libraries/Randoms
>
> http://learnyouahaskell.com/input-and-output#randomness
>
>
> The main thing to realise is that random number generators are pure and
> predictable. Given the state of a random number generator, if you ask
> for a random number, it always gives the same answer. It has to, because
> it is pure.
>
> Let's make one, and seed it with the starting state 12345
>
> ghci> :module System.Random
> ghci> let g0 = mkStdGen 12345
>
> Now we can ask for the next random number in the sequence:
>
> ghci> let (n1, g1) = next g0
> ghci> n1
> 493972152
>
> Now of course if we asked for the random number from g0 again then we
> must get the same result. But notice that when we use 'next' it also
> gives us back g1 which is the next state of the random number generator.
>
> ghci> let (n2, g2) = next g1
> ghci> n2
> 335387100
>
> So this is the basic way that random number generators work in a pure
> language. The generator has to be passed around the pure function, for
> example from one recursion to the next.
>
> So you end up with pure functions like:
>
> shuffle :: RandomGen g => g -> [x] -> [x]
>
> Another approach is to hide the 'g' inside a monad. That's what
> MonadRandom is all about. eg:
>
> shuffle :: [x] -> Rand [x]
>
> The tutorials above explain about the other random functions, for
> getting values of different types (not just Int) and restricted ranges
> of number etc.
>
> Of course at some point you want to seed the random number generator
> with some initial genuinely random value (not like the 12345 we used
> above). That is the only place in your random-handling code that needs
> to do IO. All the rest of it can be pure.
>
> Duncan
>
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