RosettaCodeData/Task/Evolutionary-algorithm/Haskell/evolutionary-algorithm-1.hs

49 lines
1.5 KiB
Haskell

import System.Random
import Control.Monad
import Data.List
import Data.Ord
import Data.Array
showNum :: (Num a, Show a) => Int -> a -> String
showNum w = until ((>w-1).length) (' ':) . show
replace :: Int -> a -> [a] -> [a]
replace n c ls = take (n-1) ls ++ [c] ++ drop n ls
target = "METHINKS IT IS LIKE A WEASEL"
pfit = length target
mutateRate = 20
popsize = 100
charSet = listArray (0,26) $ ' ': ['A'..'Z'] :: Array Int Char
fitness = length . filter id . zipWith (==) target
printRes i g = putStrLn $
"gen:" ++ showNum 4 i ++ " "
++ "fitn:" ++ showNum 4 (round $ 100 * fromIntegral s / fromIntegral pfit ) ++ "% "
++ show g
where s = fitness g
mutate :: [Char] -> Int -> IO [Char]
mutate g mr = do
let r = length g
chances <- replicateM r $ randomRIO (1,mr)
let pos = elemIndices 1 chances
chrs <- replicateM (length pos) $ randomRIO (bounds charSet)
let nchrs = map (charSet!) chrs
return $ foldl (\ng (p,c) -> replace (p+1) c ng) g (zip pos nchrs)
evolve :: [Char] -> Int -> Int -> IO ()
evolve parent gen mr = do
when ((gen-1) `mod` 20 == 0) $ printRes (gen-1) parent
children <- replicateM popsize (mutate parent mr)
let child = maximumBy (comparing fitness) (parent:children)
if fitness child == pfit then printRes gen child
else evolve child (succ gen) mr
main = do
let r = length target
genes <- replicateM r $ randomRIO (bounds charSet)
let parent = map (charSet!) genes
evolve parent 1 mutateRate