nondeterminism alternatives and similar packages
Based on the "AI" category.
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tensor-safe
A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras. -
moo
Genetic algorithm library for Haskell. Binary and continuous (real-coded) GAs. Binary GAs: binary and Gray encoding; point mutation; one-point, two-point, and uniform crossover. Continuous GAs: Gaussian mutation; BLX-α, UNDX, and SBX crossover. Selection operators: roulette, tournament, and stochastic universal sampling (SUS); with optional niching, ranking, and scaling. Replacement strategies: generational with elitism and steady state. Constrained optimization: random constrained initialization, death penalty, constrained selection without a penalty function. Multi-objective optimization: NSGA-II and constrained NSGA-II. -
HaVSA
HaVSA (Have-Saa) is a Haskell implementation of the Version Space Algebra Machine Learning technique described by Tessa Lau. -
Etage
A general data-flow framework featuring nondeterminism, laziness and neurological pseudo-terminology.
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README
Nondeterminism
This package is available via Hackage where its documentation resides.
This provides nondeterministic computations in Haskell. It implements
an Amb
monad in which you can perform nondeterministic choices along
with a monad transformer version, AmbT
.
Amb
An example which finds Pythagorean triplets up to a certain size, project Euler problem 9.
import Control.Monad
import Control.Monad.Amb
pyTriple :: (Num t, Ord t) => t -> Amb r (t, t, t)
pyTriple n = do a <- anIntegerBetween 1 n
b <- anIntegerBetween (a + 1) n
c <- anIntegerBetween (b + 1) n
when (a*a + b*b /= c*c) empty
return (a,b,c)
length $ allValues $ pyTriple 100
More examples can be found in tests/test.hs
.
Future
- allValues is not lazy in its return value