CarneadesDSL
simple-genetic-algorithm
| CarneadesDSL | simple-genetic-algorithm | |
|---|---|---|
| - | - | |
| 2 | 12 | |
| - | - | |
| 0.0 | 0.0 | |
| 4 months ago | about 8 years ago | |
| Haskell | Haskell | |
| BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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.
CarneadesDSL
We haven't tracked posts mentioning CarneadesDSL yet.
Tracking mentions began in Dec 2020.
simple-genetic-algorithm
We haven't tracked posts mentioning simple-genetic-algorithm yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
fei-dataiter - Data Loading API of mxnet in Haskell
simple-genetic-algorithm-mr - Fork of simple-genetic-algorithm using MonadRandom
huff - A fast-forward based planner for Haskell
simple-neural-networks - Simple parallel neural networks implementation in pure Haskell [GET https://api.github.com/repos/afiskon/simple-neural-networks: 404 - Not Found // See: https://docs.github.com/rest/repos/repos#get-a-repository]
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.
hnn - haskell neural network library