So i was reading "Programming Game AI by Example" by Mat Buckland
(http://www.ai-junkie.com/books/toc_pgaibe.html) and decided to rewrite
his chapter on Fuzzy logic in haskell (from C++).
My initial impression: its one of those scenarios where OOP grossly over
complicates things
Heres an example taken from the book: An agent needs to decide what
weapon to use based on his distance from the target and the amount of
ammo each has. The result is in the desirability domain (0-100).
http://code.haskell.org/~hexpuem/fuzzyLogic/AI/Logic/Fuzzy/Example.hs
An excerpt:
------------------------------------
weapons = [ Weapon "RocketLauncher" 9 rocketLauncher,
Weapon "ShotGun" 13 shotgun,
Weapon "AssaultRifle" 120 assaultRifle,
Weapon "SniperRifle" 7 sniperRifle,
Weapon "Knife" 1 knife ]
chooseWeapon dist = maximum ratings
where
ratings = [ (f dist ammo, n) | Weapon n ammo f <- weapons ]
------------------------------------
shotgun :: Double -> Double -> Double
shotgun dist ammo =
unfuzz desireDom $ rules (fuzz distDom dist) (fuzz ammoDom ammo)
where
rules :: Fuzzy Distances -> Fuzzy Ammo -> FL Desirability
rules distance ammo = do
distance `is` SniperSuited =>> Pointless
distance `is` Far =>> Undesirable
distance `is` Medium =>> Undesirable
distance `is` Melee =>> Undesirable
(distance `fairly` Near) & (ammo `fairly` High) =>> VeryDesirable
(distance `fairly` Near) & (ammo `fairly` Good) =>> Desirable
(distance `fairly` Near) & (ammo `is` Low) =>> Undesirable
------------------------------------
Full code at http://code.haskell.org/~hexpuem/fuzzyLogic/.
Suggestions welcome - maybe it'd be useful to upload to hackage at some
point.
It only supports triangle, shoulder, and singleton memberships at the
moment.
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