nondeterminism VS HSGEP

Compare nondeterminism vs HSGEP and see what are their differences.

nondeterminism

Nondeterministic computations in Haskell (by abarbu)
AI

HSGEP

Haskell Gene Expression Programming Library (by mjsottile)
AI
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nondeterminism HSGEP
1 -
7 10
- -
0.0 0.0
almost 2 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.

nondeterminism

Posts with mentions or reviews of nondeterminism. We have used some of these posts to build our list of alternatives and similar projects.
  • McCarthy's Ambiguous Operator
    1 project | news.ycombinator.com | 12 Sep 2022
    I found this after wondering why the main data structure in [this package](https://github.com/abarbu/nondeterminism-haskell) was called `Amb`. Seems like this operator can be used to generate a constraint-solving engine elegantly.

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 nondeterminism and HSGEP you can also consider the following projects:

hnn - haskell neural network library

creatur - Framework for artificial life and other evolutionary algorithms.

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.

genprog - Genetic programming library

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

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.

HOpenCV - Haskell bindings for OpenCV

grenade - Deep Learning in Haskell