// Create a new generation
public void Generate()
{
NeuralNetwork[] temp = new NeuralNetwork[alessiaAIs.Count];
// Refill the population with children from the mating pool
for (int i = 0; i < alessiaAIs.Count - 1; i++)
{
if (i == bestAlessiaAI)
{
temp[i] = alessiaAIs[i].GetComponent <Alessia_AI_DNA>().neuralNetwork;
}
else
{
Alessia_AI_DNA partnerA = PickOne(alessiaAIs);
Alessia_AI_DNA partnerB = PickOne(alessiaAIs);
NeuralNetwork child = partnerA.CrossOver(partnerB);
Mutate(ref child, mutationRate);
temp[i] = child;
}
}
for (int i = 0; i < alessiaAIs.Count - 1; i++)
{
alessiaAIs[i].GetComponent <Alessia_AI_DNA>().neuralNetwork = temp[i];
}
alessiaAIs[alessiaAIs.Count - 1].GetComponent <Alessia_AI_DNA>().neuralNetwork = new NeuralNetwork(this.inputNodes, this.hiddenNodes, this.outputNodes);
//if (matingPool.Count != 0)
{
generations++;
}
RestartAlessiaAIs(spawnPosition);
}
// Start is called before the first frame update
void Start()
{
rigidbody = GetComponent <Rigidbody>();
alessia_AI_DNA = GetComponent <Alessia_AI_DNA>();
alessiaController = GetComponent <AlessiaController>();
//TEST
//carDNA.InitCar(5, 5, 2);
}
// Crossover
public NeuralNetwork CrossOver(Alessia_AI_DNA partner)
{
// A new child
NeuralNetwork child = new NeuralNetwork(neuralNetwork.inputNodes, neuralNetwork.hiddenNodes, neuralNetwork.outputNodes);
//Do crossover
DoCrossOver(ref child.ihWeights, neuralNetwork.ihWeights, partner.neuralNetwork.ihWeights);
DoCrossOver(ref child.hoWeights, neuralNetwork.hoWeights, partner.neuralNetwork.hoWeights);
DoCrossOver(ref child.biasH, neuralNetwork.biasH, partner.neuralNetwork.biasH);
DoCrossOver(ref child.biasO, neuralNetwork.biasO, partner.neuralNetwork.biasO);
return(child);
}
