private void Start()
{
int seed = Random.Range(0, 10000);
Random.InitState(seed);
Debug.Log("Seed: " + seed);
CPPN cppn1 = new CPPN(3, 2, neuronIA, connectionIA);
cppn1.printGenome();
CPPN cppn2 = new CPPN(3, 2, neuronIA, connectionIA);
cppn2.printGenome();
CPPN.Genome genome = CPPNLib.Crossover(cppn1.genome, cppn2.genome);
genome.mutate(neuronIA, connectionIA);
cppn = new CPPN(genome, neuronIA, connectionIA);
cppn.printGenome();
Debug.Log("fitness: " + Fitness(cppn, 100));
rb = GetComponent <Rigidbody>();
}
private CPPN createFromWinnerAndGetWinner(CPPN cppn, int amount, int evaluationIterations)
{
CPPN winner = cppn;
float winnerScore = fitness(cppn, evaluationIterations);
for (int i = 0; i < amount; i++)
{
CPPN.Genome genome = cppn.genome.copy();
genome.mutate(neuronIA, connectionIA);
CPPN newCppn = new CPPN(genome, neuronIA, connectionIA);
float score = fitness(newCppn, evaluationIterations);
if (score > winnerScore)
{
winner = newCppn;
winnerScore = score;
}
}
Debug.Log("Won with " + winnerScore);
return(winner);
}
public static CPPN.Genome Crossover(CPPN.Genome p0, CPPN.Genome p1)
{
CPPN.Genome outputGenome = new CPPN.Genome();
// Combine neurons
//Debug.Log("Keys1: " + p0.neuronGenes.Keys.Count);
foreach (var n in p0.neuronGenes.Keys)
{
//Debug.Log(" - " + n);
if (p1.neuronGenes.ContainsKey(n)) // Contained in both
{
if (MyMath.randomBool())
{
outputGenome.neuronGenes.Add(n, p0.neuronGenes[n]);
}
else
{
outputGenome.neuronGenes.Add(n, p1.neuronGenes[n]);
}
}
else
{
outputGenome.neuronGenes.Add(n, p0.neuronGenes[n]); // Unique for p0
}
}
//Debug.Log("Keys2: " + p1.neuronGenes.Keys.Count);
foreach (var n in p1.neuronGenes.Keys)
{
//Debug.Log(" - " + n);
if (!outputGenome.neuronGenes.ContainsKey(n))
{
outputGenome.neuronGenes.Add(n, p1.neuronGenes[n]); // Unique for p1
}
}
// Combine connections
foreach (var n in p0.connectionGenes.Keys)
{
if (p1.connectionGenes.ContainsKey(n)) // Contained in both
{
if (MyMath.randomBool())
{
outputGenome.connectionGenes.Add(n, p0.connectionGenes[n]);
}
else
{
outputGenome.connectionGenes.Add(n, p1.connectionGenes[n]);
}
}
else
{
outputGenome.connectionGenes.Add(n, p0.connectionGenes[n]); // Unique for p0
}
}
foreach (var n in p1.neuronGenes.Keys)
{
if (!outputGenome.neuronGenes.ContainsKey(n))
{
outputGenome.connectionGenes.Add(n, p1.connectionGenes[n]); // Unique for p1
}
}
return(outputGenome);
}
