Andrew Wagner wrote:
I've got several problems which seem to have a very similar structure.
I want to find a way to abstract them to solve other problems which
can be thought about in the same way. Here they are:
http://hpaste.org/307
http://hpaste.org/308
http://hpaste.org/309
Note that these are just sketches, the programs aren't done yet. The
general structure of the problem is that an object enters a system,
interacts with different parts of the system, and eventually leaves,
and we want to monitor some statistics about the interaction, so that
we can then make some changes, and run it again, and hopefully improve
it.
I like your approach.
You have to watch out for the strictness bug in State/StateT
for this application. Try to keep your functions polymorphic -
using MonadState, as below - so it will be easy to switch
between them later as needed.
I would put a StdGen into the State. Generate the
StdGen in your main and pass it as a parameter to
your initialState function. Access it with something like
getRand :: (Random a, MonadState TheState m) => a -> a -> m a
getRand lo hi = do
s <- get
let (r, g) = randomR (lo, hi) $ randomGen s
put $ s {randomGen = g}
return r
Then write random distribution functions that look something like
theDistribution :: (MonadState TheState m) => stuff -> m [Event]
theDistribution stuff = do
...
r <- getRand lo hi
...
You will probably want to base your random distributions
on the Poisson distribution if you want your simulations
to be realistic. Here are some Wikipedia links:
http://en.wikipedia.org/wiki/Queuing_theory
http://en.wikipedia.org/wiki/Poisson_distribution
Regards,
Yitz
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