simple-genetic-algorithm VS Etage

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

simple-genetic-algorithm

Simple parallel genetic algorithm implementation in pure Haskell (by afiskon)

Etage

A general data-flow framework featuring nondeterminism, laziness and neurological pseudo-terminology. (by mitar)
AI
Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
simple-genetic-algorithm Etage
- -
12 0
- -
0.0 0.0
about 6 years ago almost 10 years ago
Haskell Haskell
BSD 3-clause "New" or "Revised" License GNU Lesser General Public License v3.0 only
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.

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.

Etage

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

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

What are some alternatives?

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

hnn - haskell neural network library

hasktorch - Tensors and neural networks in Haskell

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

keera-posture - Alleviate your back pain using Haskell and a webcam

csp - Constraint satisfaction problem (CSP) solvers for Haskell

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.

heukarya - genetic programming in haskell

GA - Haskell module for working with genetic algorithms

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

tensor-safe - A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.