heukarya VS simple-genetic-algorithm

Compare heukarya vs simple-genetic-algorithm and see what are their differences.

heukarya

genetic programming in haskell (by t3476)
AI

simple-genetic-algorithm

Simple parallel genetic algorithm implementation in pure Haskell (by afiskon)
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heukarya simple-genetic-algorithm
- -
17 12
- -
0.0 0.0
over 10 years ago about 6 years ago
Haskell Haskell
BSD 3-clause "New" or "Revised" License BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

heukarya

Posts with mentions or reviews of heukarya. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning heukarya yet.
Tracking mentions began in Dec 2020.

simple-genetic-algorithm

Posts with mentions or reviews of simple-genetic-algorithm. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning simple-genetic-algorithm yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing heukarya and simple-genetic-algorithm you can also consider the following projects:

hnn - haskell neural network library

genprog - Genetic programming library

simple-genetic-algorithm-mr - Fork of simple-genetic-algorithm using MonadRandom

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.

csp - Constraint satisfaction problem (CSP) solvers for Haskell

svm - A support vector machine implemented in Haskell.

simple-neural-networks - Simple parallel neural networks implementation in pure Haskell

opencv - Haskell binding to OpenCV-3.x

GA - Haskell module for working with genetic algorithms

svm-simple - Simplified interface to bindings-svm

liblinear-enumerator - Haskell bindings to liblinear