This repository contains a simple implementation of a genetic algorithm for evolving arbitrary types. There's a double-buffering in place to prevent unnecessary allocations and a relatively simple API around it.
It also provides a binary package for evolving []byte genomes. Under the hood, it uses a simple random binary crossover and mutation to do the trick.
In order to use this, we first need to create a "phenotype" representation which contains the dna. In this example we're using the binary package in order to evolve a string. It should implement the Evolver interface which contains Genome() and Evolve() methods, in the example here we are creating a simple text which contains the binary representation of the text itself.
// Text represents a text with a dna (text itself in this case)
type text struct {
dna evolve.Genome
}
// Genome returns the genome
func (t *text) Genome() []byte {
return t.dna
}
// Evolve updates the genome
func (t *text) Evolve(v []byte) {
t.dna = v
}Next, we'll need a fitness function to evaluate how good a genome is. In this example we're creating a fitness function for an abritrary string which simply returns a func(Evolver) float32
// fitnessFor returns a fitness function for a string
func fitnessFor(text string) evolve.Fitness {
target := []byte(text)
return func(v evolve.Evolver) float32 {
var score float32
genome := v.Genome().(*binary.Genome)
for i, v := range *genome {
if v == target[i] {
score++
}
}
return score / float32(len(target))
}
}Finally, we can wire everything together by using New() function to create a population, and evolve it by repeatedly calling Evolve() method as shown below.
func main() {
const target = "Hello World"
const n = 200
// Create a fitness function
fit := fitnessFor(target)
// Create a population
population := make([]evolve.Evolver, 0, n)
for i := 0; i < n; i++ {
population = append(population, new(text))
}
// Create a population
pop := evolve.New(population, fit, len(target))
// Evolve over many generations
for i := 0 ; i < 100000; i++ {
pop.Evolve()
}
// Get the fittest member of the population
fittest := pop.Fittest()
}Tile is licensed under the MIT License.