func main() {
flag.Parse()
rand.Seed(time.Now().UTC().UnixNano())
// Make the dummy population to train against
dummies = evogo.NewPopulation(1000, 20, 20, CreateGene)
var strongest *evogo.Individual
if *train_com {
pop := evogo.NewPopulation(100, 20, 20, CreateGene)
evogo.Train(pop, 2198, Fitness, MutateGene)
strongest = pop.Individuals()[0] // Get strongest individual
} else {
strongest = dummies.Individuals()[0]
}
for {
// Start games
var a, b string
var pa, pb player
fmt.Print("Player 1 is human or computer (h, c, q to quit): ")
fmt.Scanf("%v", &a)
if a == "q" {
return
}
fmt.Print("Player 2 is human or computer (h, c, q to quit): ")
fmt.Scanf("%v", &b)
if b == "q" {
return
}
if a == "h" {
pa = human{}
} else {
pa = NewComputer(strongest, true)
}
if b == "h" {
pb = human{}
} else {
pb = NewComputer(strongest, true)
}
winner := NewGame(pa, pb).play()
fmt.Println("The winner is player", winner, "\n\n")
}
}
func main() {
rand.Seed(time.Now().UTC().UnixNano())
// Generate a new populaation with
// 100 Individuals
// 13 Genes per individual
// And our custom CreateGene function used to make the genes
pop := evogo.NewPopulation(1000, 13, 13, CreateGene)
pop.SetShowIndividual(ShowGenes) // Give it our show function
// Call the train function and provide it with
// The population to train
// The target fitness at which to stop
// fitness function to evaluate the fitness of a particular individual
start := time.Now()
evogo.Train(pop, 0, 1000, 40, fitness, MutateGene)
elapsed := time.Since(start)
fmt.Printf("Took %s\n", elapsed)
}
