csp VS HSGEP

Compare csp vs HSGEP and see what are their differences.

csp

Constraint satisfaction problem (CSP) solvers for Haskell (by abarbu)
AI

HSGEP

Haskell Gene Expression Programming Library (by mjsottile)
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
csp HSGEP
- -
15 10
- -
0.0 0.0
about 6 years ago about 6 years ago
Haskell Mathematica
LicenseRef-LGPL 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.

csp

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

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

HSGEP

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

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

What are some alternatives?

When comparing csp and HSGEP you can also consider the following projects:

grenade - Deep Learning in Haskell

creatur - Framework for artificial life and other evolutionary algorithms.

opencv - Haskell binding to OpenCV-3.x

hopfield - hopfield

GA - Haskell module for working with genetic algorithms

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

hnn - haskell neural network library

genprog - Genetic programming library

HaVSA - HaVSA (Have-Saa) is a Haskell implementation of the Version Space Algebra Machine Learning technique described by Tessa Lau.

simple-genetic-algorithm - Simple parallel genetic algorithm implementation in pure 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.