Gentic Algorithm TypeScript implementation, customisable
Multiprocessing genetic algorithm implementation library
Architecture-free neural network library with genetic algorithm implementations
Implement Genetic Algorithm in JavaScript.
Multiprocessing genetic algorithm implementation library extension
Neural Network using Genetic Algorithm
Genetic algorithm
Simple genetic algorithm helper class. Supports asynchronous fitness evaluation.
Architecture-free neural network library with genetic algorithm implementations
a general purpose genetic algorithm, an A.I. tool useful for machine evolution and adaptation
A Genetic Algorithm
Genetic Algorithm with 'island' Diversity support
Object-oriented genetic algorithm framework
General-purpose Genetic Algorithm library
A lightweight genetic algorithm library.
Genetic algorithm in JS
Genetic Algorithm
This package provides a framework for building applications where genetic algorithm (GA) is used for solving optimization problems based on a natural selection process that mimics biological evolution.
A Genetic Algorithm AI lib for JS
A simple genetic algorithm framework for Node.
Genetic algorithm
canonical genetic algorithm implementation
Flexible Genetic Algorithm Library
Genetic Algorithm Sampler in NodeJS
A genetic algorithm implementation
A parallelized genetic algorithm runner
A comprehensive collection of metaheuristic optimization algorithms implemented in Rust
Genetic algorithm tools library
A.I. genetic algorithm implementation
A Pragmatic Global Black-Box Optimizer
Dependency Structure Matrix Genetic Algorithm II with two-edge graphical linkage model
Library to implement genetic algorithms
A generic, composable genetic algorithm framework for Rust
Proc-macro crate for the evolve genetic algorithm framework — provides the grammar! macro
Information-driven protein-protein docking using a genetic algorithm
Extra utilities for genetic-rs, including plotting and progress bars.
A Generic Algorithm Library for Ruby Language
Simple genetic algorithm for functions minimization.
A simple gem to help in the creation of genetic algorithms
== DESCRIPTION: Charlie is a library for genetic algorithms (GA) and genetic programming (GP). == FEATURES: - Quickly develop GAs by combining several parts (genotype, selection, crossover, mutation) provided by the library. - Sensible defaults are provided with any genotype, so often you only need to define a fitness function. - Easily replace any of the parts by your own code. - Test different strategies in GA, and generate reports comparing them. Example report: http://charlie.rubyforge.org/example_report.html == INSTALL: * sudo gem install charlie == EXAMPLES: This example solves a TSP problem (also quiz #142): N=5 CITIES = (0...N).map{|i| (0...N).map{|j| [i,j] } }.inject{|a,b|a+b} class TSP < PermutationGenotype(CITIES.size) def fitness d=0 (genes + [genes[0]]).each_cons(2){|a,b| a,b=CITIES[a],CITIES[b] d += Math.sqrt( (a[0]-b[0])**2 + (a[1]-b[1])**2 ) } -d # lower distance -> higher fitness. end use EdgeRecombinationCrossover, InversionMutator end Population.new(TSP,20).evolve_on_console(50) This example finds a polynomial which approximates cos(x) class Cos < TreeGenotype([proc{3*rand-1.5},:x], [:-@], [:+,:*,:-]) def fitness -[0,0.33,0.66,1].map{|x| (eval_genes(:x=>x) - Math.cos(x)).abs }.max end use TournamentSelection(4) end Population.new(Cos).evolve_on_console(500)
Framework for genetic algorithm fast development
Genetica is a library to create and use Genetics Algorithms with Ruby.
Simple Framework of Genetic Algorithm
Providing an expressive DSL to illustrate genetic algorithm problems and sets of default methods.
Genetic Algorithm Pool Selection.
Evolve provides a simple and readable interface to make genetic algorithm optimization easy
Darwinning provides tools to build genetic algorithm solutions using a Gene, Organism, and Population structure.
Optimise anything that responds to 'fitness' and takes a hash
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