private static Network breed(int parentA, int parentB)
{
List<Edge> childEdges = new List<Edge> ();
int AIndex = 0;
int BIndex = 0;
//merge genomes
while (AIndex < networks[parentA].edges.Count && BIndex < networks[parentB].edges.Count) {
if (networks [parentA].edges [AIndex].innovation == networks [parentB].edges [BIndex].innovation) {
if (rand.Next (0, 2) == 0) {
Edge e = new Edge(networks[parentA].edges[AIndex].inNeuron,networks[parentA].edges[AIndex].outNeuron,networks[parentA].edges[AIndex].weight, networks[parentA].edges[AIndex].isEnabled,networks[parentA].edges[AIndex].innovation);
childEdges.Add (e);
} else {
Edge e = new Edge(networks[parentB].edges[BIndex].inNeuron,networks[parentB].edges[BIndex].outNeuron,networks[parentB].edges[BIndex].weight, networks[parentB].edges[BIndex].isEnabled,networks[parentB].edges[BIndex].innovation);
childEdges.Add (e);
}
AIndex++;
BIndex++;
} else if (networks [parentA].edges [AIndex].innovation > networks [parentB].edges [BIndex].innovation) {
BIndex++;
} else {
Edge e = new Edge(networks[parentA].edges[AIndex].inNeuron,networks[parentA].edges[AIndex].outNeuron,networks[parentA].edges[AIndex].weight, networks[parentA].edges[AIndex].isEnabled,networks[parentA].edges[AIndex].innovation);
childEdges.Add (e);
AIndex++;
}
}
//excess edges left over from dominant parent
if (BIndex == networks [parentB].edges.Count) {
for (int i=AIndex; i<networks[parentA].edges.Count; i++) {
Edge e = new Edge(networks[parentA].edges[i].inNeuron,networks[parentA].edges[i].outNeuron,networks[parentA].edges[i].weight, networks[parentA].edges[i].isEnabled,networks[parentA].edges[i].innovation);
childEdges.Add (e);
}
}
//perturb it
double rand01 = rand.NextDouble ();
if (rand01 < perturbChance) {
double perturbAmount = (rand.NextDouble () * perturbPercent * 2.0 - perturbPercent);
for (int i=0; i<childEdges.Count; i++) {
//perturb it! sore aru
if(rand.NextDouble() < 0.9){
childEdges [i].weight = childEdges [i].weight + perturbAmount;
}
else{
//give weight a new value;
childEdges [i].weight = randomEdgeWeight();
}
if (!childEdges [i].isEnabled) {
rand01 = rand.NextDouble ();
if (rand01 < enableMutationChance) {
childEdges [i].isEnabled = true;
}
}
}
}
//create the child network
Network net = new Network ();
//add inputs
for(int j=0;j<inputN;j++){
Neuron n = new Neuron();
net.addNeuron(n);
net.addInput(j);
}
//add outputs
for(int j=0;j<outputN;j++){
Neuron n = new Neuron();
net.addNeuron(n);
net.addOutput(inputN + j);
}
for (int j=0; j<(neuronN - inputN - outputN); j++) {
Neuron n = new Neuron ();
net.addNeuron (n);
}
for(int i=0;i<childEdges.Count;i++){
bool flag = net.addEdge(childEdges[i].inNeuron, childEdges[i].outNeuron, childEdges[i].weight, childEdges[i].innovation);
if(flag==false){
//Console.WriteLine("wtf add edge failed");
}
}
//new links
double rand2 = rand.NextDouble();
if (rand2 < linkMutationChance) {
int tCount = 0;
while(tCount <30){
int inputNode = rand.Next(0,neuronN - outputN);
if(inputNode >= inputN){
inputNode += outputN;
}
int outputNode = rand.Next (inputN, neuronN);
if(net.checkEdge(inputNode, outputNode)){
//add edge if the edge is connected to the input.
if(net.neurons[inputNode].inputEdges.Count > 0 || inputNode < inputN){
bool tb = net.addEdge(inputNode, outputNode, randomEdgeWeight(), getInnovation(inputNode, outputNode));
if(tb){
tCount = 20;
}
}
}
tCount++;
}
}
//new node
rand2 = rand.NextDouble ();
if (rand2 < nodeMutationChance) {
int tCount = 0;
while(tCount < 10){
int randomEdge = rand.Next(0,net.edges.Count);
bool flag = true;
int randomEdgeIn = net.edges[randomEdge].inNeuron;
int randomEdgeOut = net.edges[randomEdge].outNeuron;
//check if there already exists a node that does the same thing
for(int i=0;i<innovationInputs.Count;i++){
if(innovationInputs[i] == randomEdgeIn){
for(int j=0;j<innovationInputs.Count;j++){
if(innovationInputs[j] == innovationOutputs[i]){
if(innovationOutputs[j] == randomEdgeOut){
flag = false;
}
}
}
}
}
//create new node
if(flag){
net.edges[randomEdge].isEnabled = false;
Neuron tN = new Neuron();
net.addNeuron(tN);
bool tb = net.addEdge(net.edges[randomEdge].inNeuron, neuronN, randomEdgeWeight(), getInnovation(net.edges[randomEdge].inNeuron, neuronN));
bool tc = net.addEdge(neuronN, net.edges[randomEdge].outNeuron, randomEdgeWeight(), getInnovation(neuronN, net.edges[randomEdge].outNeuron));
if(!tb || !tc){
//Console.WriteLine("add Edge failed");
}
neuronN++;
tCount = 20;
net.printNetwork();
}
tCount++;
}
}
return net;
}
