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royalroad.go
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royalroad.go
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package main
import "fmt"
import "math/rand"
import "time"
// Fitness
type FitnessCalculator struct {
solution Individual
}
func (fc *FitnessCalculator) scoreFitness(ind Individual) int {
score := 0
for i := 0; i < 64; i++ {
if fc.solution.genes[i] == ind.genes[i] {
score++
}
}
return score
}
func (fc *FitnessCalculator) getMaxFitness() int {
return 64
}
// Individuals
type Individual struct {
genes [64]int
}
func (ind *Individual) generateIndividual() {
var buffer [64]int
for i := 0; i < 64; i++ {
buffer[i] = rand.Intn(2)
}
ind.genes = buffer
}
func (ind *Individual) getGene(index int) int {
return ind.genes[index]
}
func (ind *Individual) setGene(index int, value int) {
ind.genes[index] = value
}
func (ind *Individual) size() int {
return len(ind.genes)
}
// Populations
type Population struct {
individuals []Individual
}
func (pop *Population) initialize(size int, init bool) {
if !init {
return
}
for i := 0; i < size; i++ {
ind := Individual{}
ind.generateIndividual()
pop.addIndividual(ind)
}
}
func (pop *Population) addIndividual(ind Individual) {
pop.individuals = append(pop.individuals, ind)
}
func (pop *Population) getFittest(fc FitnessCalculator) Individual {
fittest := pop.individuals[0]
for i := 0; i < len(pop.individuals); i++ {
if fc.scoreFitness(pop.individuals[i]) > fc.scoreFitness(fittest) {
fittest = pop.individuals[i]
}
}
return fittest
}
func (pop *Population) getRandom() Individual {
return pop.individuals[rand.Intn(20)]
}
func (pop *Population) size() int {
return len(pop.individuals)
}
// Algorithms
type Algorithm struct {
mutationRate float32
uniformRate float32
elitism bool
tournamentSize int
fitnessCalc FitnessCalculator
}
func (algor *Algorithm) evolvePopulation(pop Population) Population {
newPopulation := Population{}
elitismOffset := 0
if algor.elitism {
newPopulation.addIndividual(pop.getFittest(algor.fitnessCalc))
elitismOffset = 1
}
for i := elitismOffset; i < pop.size(); i++ {
individual1 := algor.tournamentSelection(pop)
individual2 := algor.tournamentSelection(pop)
newIndividual := algor.crossover(individual1, individual2)
newPopulation.addIndividual(newIndividual)
}
for i := 0; i < newPopulation.size(); i++ {
if algor.elitism && i == 0 {
continue
}
algor.mutate(&newPopulation.individuals[i])
}
return newPopulation
}
func (algor *Algorithm) mutate(ind *Individual) {
for i := 0; i < ind.size(); i++ {
if rand.Float32() <= algor.mutationRate {
ind.setGene(i, rand.Intn(2))
}
}
}
func (algor *Algorithm) crossover(individual1 Individual, individual2 Individual) Individual {
hybrid := Individual{}
for i := 0; i < individual1.size(); i++ {
if rand.Float32() <= algor.uniformRate {
hybrid.setGene(i, individual1.getGene(i))
} else {
hybrid.setGene(i, individual2.getGene(i))
}
}
return hybrid
}
func (algor *Algorithm) tournamentSelection(pop Population) Individual {
tournament := new(Population)
for i := 0; i < algor.tournamentSize; i++ {
tournament.addIndividual(pop.getRandom())
}
return tournament.getFittest(algor.fitnessCalc)
}
func main() {
fmt.Println("Royal Road!")
rand.Seed(time.Now().UTC().UnixNano())
solution := Individual{}
solution.generateIndividual()
fitnessCalc := FitnessCalculator{solution}
algorithm := Algorithm{0.015, 0.5, true, 5, fitnessCalc}
generationCount := 0
population := Population{}
population.initialize(20, true)
for {
if fitnessCalc.scoreFitness(population.getFittest(fitnessCalc)) == fitnessCalc.getMaxFitness() {
break
}
generationCount++
population = algorithm.evolvePopulation(population)
fmt.Println("generation & fitness", generationCount, fitnessCalc.scoreFitness(population.getFittest(fitnessCalc)))
}
fmt.Println("answer found in generation:", generationCount)
}