On Sat, Dec 18, 2010 at 04:11:02AM +0000, Amy de Buitléir wrote:
Q2: The "Animal" type includes a "brain" component. I implemented that as a simple list, but perhaps it would be better to use a monad here?
I am not 100% sure I understand this question, but I'm pretty sure the answer is "no", the way you have defined the Animal type looks fine to me.
Q1: My implementation of "simulateBrain" seems clumsy. Is there a better way to do this?
Well, it's fine for what it is, but I would generalize it a bit, to make it more widely applicable. The key challenge is that stimulateBrain is supposed to be a computation using a whole Animal as state, but it is to be defined in terms of a computation operating simply on the Brain as state. Unfortunately that means the types will not match, so we need some sort of adapter, as you figured out. But this problem is not specific to Animal and Brain: what if later we wanted to use a computation which has access only to the Pancreas, etc.? We can define a generic adapter as follows: withComponent :: (RandomGen g) => -- | "Extractor" function to allow us to extract the piece of state s' -- from the larger state s (s -> s') -> -- | "Setter" function to update the larger state with a new s' (s' -> s -> s) -> -- | The state computation to run over the smaller state... RandT g (State s') a -> -- | ...which we can now use as a state computation over the larger state RandT g (State s) a withComponent extract set m = do s <- get g <- getSplit let (a, s') = runState (evalRandT m g) (extract s) put $ set s' s return a Now stimulateBrain is just stimulateBrain :: (RandomGen g) => Int -> [Double] -> RandT g (State Animal) () stimulateBrain n xs = withComponent brain (\b a -> a { brain = b }) (stimulate n xs) and you can also easily write stimulatePancreas or whatever. We can generalize this further in two ways, which I will leave for you to explore if you are interested: (1) use something like data-accessor for automatically deriving the 'extractor' and 'setter' functions. (2) generalizing withComponent so that it works with other monad stacks. -Brent
Thank you, Amy
----- SAMPLE CODE -----
{-# LANGUAGE PackageImports, RankNTypes, FlexibleContexts #-}
import "mtl" Control.Monad.State import Control.Monad.Random
type Neuron = Int -- The real type is more complex
-- An "Alife" animal data Animal = Animal { brain :: [Neuron] -- There are other fields too, of course } deriving (Show, Read)
-- | Stimulates an animal's brain, and allows it to react. stimulateBrain :: (RandomGen g) -- | The number of cycles => Int -- | The signals to apply to the sensor neurons -> [Double] -- | The animal -> RandT g (State Animal) () stimulateBrain n xs = do c <- get g <- getSplit let b' = execState (evalRandT (stimulate n xs) g) (brain c) put $ c{brain=b'}
-- | Feeds some input signals into a brain, and allow it to react. stimulate :: (RandomGen g) -- | The number of cycles => Int -- | The signals to apply to the sensor neurons -> [Double] -- | The neuron states -> RandT g (State [Neuron]) () stimulate k xs = return () -- The real implementation is more complex
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