public SpeciesBreedingPool(GenomeNEAT genome, int id)
{
agentList = new List <Agent>();
templateGenome = genome;
speciesID = id;
nextAgentIndex = 0;
}
public GenomeNEAT InitializeRandomBrain(int numInputNodes, int numOutputNodes)
{
sourceGenome = new GenomeNEAT(numInputNodes, numOutputNodes); // create blank genome with no connections
sourceGenome.CreateMinimumRandomConnections(); // Add links to each output node froma random input node
return(sourceGenome);
}
public void SortAgentIntoBreedingPool(Agent agent)
{
bool speciesGenomeMatch = false;
for (int s = 0; s < speciesBreedingPoolList.Count; s++)
{
float geneticDistance = GenomeNEAT.MeasureGeneticDistance(agent.brainGenome, speciesBreedingPoolList[s].templateGenome, 0.425f, 0.425f, 0.15f, 0f, 0f, 1f);
if (geneticDistance < 1f) //speciesSimilarityThreshold) { // !!! figure out how/where to place this attribute or get a ref from crossoverManager
{
speciesGenomeMatch = true;
//agent.speciesID = speciesBreedingPoolList[s].speciesID; // this is done inside the AddNewAgent method below v v v
speciesBreedingPoolList[s].AddNewAgent(agent);
//Debug.Log("SortAgentIntoBreedingPool dist: " + geneticDistance.ToString() + ", speciesIDs: " + agent.speciesID.ToString() + ", " + speciesBreedingPoolList[s].speciesID.ToString());
break;
}
}
if (!speciesGenomeMatch)
{
//Debug.Log("POPULATION SortAgentIntoBreedingPool NO MATCH!!! -- creating new BreedingPool ");
SpeciesBreedingPool newSpeciesBreedingPool = new SpeciesBreedingPool(agent.brainGenome, GetNextSpeciesID()); // creates new speciesPool modeled on this agent's genome
newSpeciesBreedingPool.AddNewAgent(agent); // add this agent to breeding pool
speciesBreedingPoolList.Add(newSpeciesBreedingPool); // add new speciesPool to the population's list of all active species
}
}
public Species(Agent newAgent)
{
id = nextID;
nextID++;
templateGenome = newAgent.brainGenome;
AddNewMember(newAgent);
}
public override object Read(ES2Reader reader)
{
GenomeNEAT data = new GenomeNEAT();
Read(reader, data);
return(data);
}
public Species(Agent newAgent) {
id = nextID;
nextID++;
templateGenome = newAgent.brainGenome;
AddNewMember(newAgent);
}
public GenomeNEAT InitializeNewBrain(int numInputNodes, int numHiddenNodes, int numOutputNodes, float connectedness, bool randomWeights)
{
sourceGenome = new GenomeNEAT(numInputNodes, numHiddenNodes, numOutputNodes); // create blank genome with no connections
sourceGenome.CreateInitialConnections(connectedness, randomWeights);
//Debug.Log("InitializeBlankBrain #nodes: " + sourceGenome.nodeNEATList.Count.ToString() + ", #links: " + sourceGenome.linkNEATList.Count.ToString());
return(sourceGenome);
}
public override void Write(object obj, ES2Writer writer)
{
GenomeNEAT data = (GenomeNEAT)obj;
// Add your writer.Write calls here.
writer.Write(0); // Version 0 is current version number
// Make sure to edit Read() function to properly handle version control!
// VERSION 0:
writer.Write(data.nodeNEATList);
writer.Write(data.linkNEATList);
}
public override void Read(ES2Reader reader, object c)
{
GenomeNEAT data = (GenomeNEAT)c;
// Add your reader.Read calls here to read the data into the object.
// Read the version number.
int fileVersion = reader.Read <int>();
// VERSION 0:
if (fileVersion >= 0)
{
data.nodeNEATList = reader.ReadList <GeneNodeNEAT>();
data.linkNEATList = reader.ReadList <GeneLinkNEAT>();
}
}
public GenomeNEAT InitializeBlankBrain(int numInputNodes, int numOutputNodes)
{
sourceGenome = new GenomeNEAT(numInputNodes, numOutputNodes); // create blank genome with no connections
/*int numNewLinks = 0;
* int numNewNodes = 0;
* for(int i = 0; i < numNewLinks; i++) {
* sourceGenome.AddNewRandomLink(0);
* }
* for (int j = 0; j < numNewNodes; j++) {
* sourceGenome.AddNewRandomNode(0);
* }*/
//Debug.Log("InitializeBlankBrain #nodes: " + sourceGenome.nodeNEATList.Count.ToString() + ", #links: " + sourceGenome.linkNEATList.Count.ToString());
return(sourceGenome);
}
public void PerformBodyMutation(ref CritterGenome bodyGenome, ref GenomeNEAT brainGenome) {
int numBodyMutations = 0;
//float attachDirMutationMultiplier = 0.1f;
//float restAngleDirMutationMultiplier = 0.1f;
float jointAngleTypeMultiplier = 0.5f;
List<int> nodesToDelete = new List<int>();
for (int i = 0; i < bodyGenome.CritterNodeList.Count; i++) {
// Segment Proportions:
if(CheckForMutation(segmentProportionChance * bodyMutationBlastModifier)) { // X
bodyGenome.CritterNodeList[i].dimensions.x = MutateBodyFloatMult(bodyGenome.CritterNodeList[i].dimensions.x);
numBodyMutations++;
}
if (CheckForMutation(segmentProportionChance * bodyMutationBlastModifier)) { // Y
bodyGenome.CritterNodeList[i].dimensions.y = MutateBodyFloatMult(bodyGenome.CritterNodeList[i].dimensions.y);
numBodyMutations++;
}
if (CheckForMutation(segmentProportionChance * bodyMutationBlastModifier)) { // Z
bodyGenome.CritterNodeList[i].dimensions.z = MutateBodyFloatMult(bodyGenome.CritterNodeList[i].dimensions.z);
numBodyMutations++;
}
if(i > 0) { // NOT THE ROOT SEGMENT!:
// REMOVE SEGMENT!!!!
if(CheckForMutation(removeSegmentChance * bodyMutationBlastModifier)) { // Can't delete Root Segment
// Add this nodeID into queue for deletion at the end of mutation, to avoid shortening NodeList while traversing it:
nodesToDelete.Add(i);
}
else {
// Segment Attach Settings:
if (CheckForMutation(segmentAttachSettingsChance * bodyMutationBlastModifier)) { // Position X
bodyGenome.CritterNodeList[i].jointLink.attachDir = MutateBodyVector3Normalized(bodyGenome.CritterNodeList[i].jointLink.attachDir);
numBodyMutations++;
}
if (CheckForMutation(segmentAttachSettingsChance * bodyMutationBlastModifier)) { // Orientation X
bodyGenome.CritterNodeList[i].jointLink.restAngleDir = MutateBodyVector3Normalized(bodyGenome.CritterNodeList[i].jointLink.restAngleDir);
numBodyMutations++;
}
// Joint Settings:
if (CheckForMutation(jointSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.CritterNodeList[i].jointLink.jointLimitPrimary = MutateBodyFloatMult(bodyGenome.CritterNodeList[i].jointLink.jointLimitPrimary);
}
if (CheckForMutation(jointSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.CritterNodeList[i].jointLink.jointLimitSecondary = MutateBodyFloatMult(bodyGenome.CritterNodeList[i].jointLink.jointLimitSecondary);
}
if (CheckForMutation(jointSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.CritterNodeList[i].jointLink.recursionScalingFactor = MutateBodyFloatMult(bodyGenome.CritterNodeList[i].jointLink.recursionScalingFactor);
}
// Joint Hinge TYPE!!!! --- how to handle this???
if (CheckForMutation(jointSettingsChance * jointAngleTypeMultiplier * bodyMutationBlastModifier)) {
int jointTypeInt = Mathf.RoundToInt(UnityEngine.Random.Range(0f, 4f));
bodyGenome.CritterNodeList[i].jointLink.jointType = (CritterJointLink.JointType)jointTypeInt;
Debug.Log(i.ToString() + " Mutated to JointType: " + bodyGenome.CritterNodeList[i].jointLink.jointType);
}
// RECURSION:
if (CheckForMutation(recursionChance * bodyMutationBlastModifier)) {
int addRemove = Mathf.RoundToInt(UnityEngine.Random.Range(0f, 1f)) * 2 - 1; // either -1 or 1
//addRemove = 1; // TEMPORARY!!! testing add recursion
if (bodyGenome.CritterNodeList[i].jointLink.numberOfRecursions + addRemove < 0 || bodyGenome.CritterNodeList[i].jointLink.numberOfRecursions + addRemove > 3) {
// Do Nothing, tried to change numRecursions beyond the CAP
}
else { // It's all good -- PROCEED:
bodyGenome.CritterNodeList[i].jointLink.numberOfRecursions += addRemove;
numBodyMutations++;
if (addRemove > 0) { // Created an additional Recursion -- Need to ADD new BrainNodes:
//int numNodesBefore = brainGenome.nodeNEATList.Count;
//brainGenome.AdjustBrainAfterBodyChange(bodyGenome);
//int numNodesAfter = brainGenome.nodeNEATList.Count;
//Debug.Log("MUTATION RECURSION! b4#: " + numNodesBefore.ToString() + ", after#: " + numNodesAfter.ToString());
}
else { // REMOVED a Recursion -- Need to REMOVE BrainNodes:
//brainGenome.AdjustBrainRemovedRecursion(bodyGenome, i);
}
}
// NEED TO FIX BRAIN!!! -- how to preserve existing wiring while adding new neurons that may re-order?
// Do I need to save a reference to segment/nodes within each input/output neuron?
}
// SYMMETRY
if (CheckForMutation(symmetryChance * bodyMutationBlastModifier)) {
int symmetryType = Mathf.RoundToInt(UnityEngine.Random.Range(0f, 2f)); // 0=none,1=x, or 2=y
Debug.Log("Mutated Symmetry! " + bodyGenome.CritterNodeList[i].jointLink.symmetryType.ToString() + " => " + ((CritterJointLink.SymmetryType)symmetryType).ToString());
bodyGenome.CritterNodeList[i].jointLink.symmetryType = (CritterJointLink.SymmetryType)symmetryType;
}
// EXTRA -- recursion forward, only attach to tail
}
// CREATE NEW ADD-ON!! On this segment
if (CheckForMutation(newAddonChance * bodyMutationBlastModifier)) {
// Which types can be created automatically??
//
int randomAddon = Mathf.RoundToInt(UnityEngine.Random.Range(0f, 1f));
switch (randomAddon) {
case 0:
AddonOscillatorInput newOscillatorInput = new AddonOscillatorInput(i, GetNextAddonInnov());
bodyGenome.addonOscillatorInputList.Add(newOscillatorInput);
break;
case 1:
AddonValueInput newValueInput = new AddonValueInput(i, GetNextAddonInnov());
bodyGenome.addonValueInputList.Add(newValueInput);
break;
default:
break;
}
Debug.Log("NEW ADDON! " + randomAddon.ToString() + ", segmentNode: " + i.ToString());
}
}
}
for(int i = 0; i < nodesToDelete.Count; i++) {
Debug.Log("DELETE SEGMENT NODE! " + i.ToString());
bodyGenome.DeleteNode(nodesToDelete[i]);
bodyGenome.RenumberNodes();
}
List<int> nodesToAddTo = new List<int>(); // After Deleting nodes, check all remaining nodes for a chance to have a child segment added:
for (int i = 0; i < bodyGenome.CritterNodeList.Count; i++) {
if (CheckForMutation(newSegmentChance * bodyMutationBlastModifier)) {
nodesToAddTo.Add(i);
}
}
for (int i = 0; i < nodesToAddTo.Count; i++) {
Vector3 attachDir = Vector3.Slerp(new Vector3(0f, 0f, 1f), UnityEngine.Random.onUnitSphere, UnityEngine.Random.Range(0f, 1f)); //ConvertWorldSpaceToAttachDir(selectedSegment, rightClickWorldPosition);
int nextID = bodyGenome.CritterNodeList.Count;
bodyGenome.AddNewNode(bodyGenome.CritterNodeList[nodesToAddTo[i]], attachDir, new Vector3(0f, 0f, 0f), nextID, GetNextNodeInnov());
// Init joint type:
bodyGenome.CritterNodeList[bodyGenome.CritterNodeList.Count - 1].jointLink.jointType = (CritterJointLink.JointType)Mathf.RoundToInt(UnityEngine.Random.Range(1, 4));
// Auto-Add-ons: -- New Segment starts with a joint angle sensor and joint Motor by default:
AddonJointAngleSensor newJointAngleSensor = new AddonJointAngleSensor(nextID, GetNextAddonInnov());
bodyGenome.addonJointAngleSensorList.Add(newJointAngleSensor);
// Motor:
AddonJointMotor newJointMotor = new AddonJointMotor(nextID, GetNextAddonInnov());
bodyGenome.addonJointMotorList.Add(newJointMotor);
Debug.Log("New SEGMENT! : " + nodesToAddTo[i].ToString());
}
// Addon Mutation:
PerformAddonMutation(ref bodyGenome, ref brainGenome);
//Debug.Log("NumBodyMutations: " + numBodyMutations.ToString());
}
public static float MeasureGeneticDistance(GenomeNEAT genomeA, GenomeNEAT genomeB, float neuronCoefficient, float linkCoefficient, float weightCoefficient, float normNeuron, float normLink, float normWeight)
{
int indexA = 0;
int indexB = 0;
float weightDeltaTotal = 0f;
float maxGenes = Mathf.Max((float)genomeA.linkNEATList.Count, (float)genomeB.linkNEATList.Count);
float matchingGenes = 0f;
//float disjointGenes = 0f;
//float excessGenes = 0f;
float linkGenes = 0f;
float neuronGenes = 0f;
int matchingNeurons = 0;
//float smallestWeightValue = 0f;
float largestWeightDelta = 0f;
// matching Links
// matching nodes/neurons
// matching activation functions?
// difference in weights
// difference in add-on settings?
// -- NEED TO GO BY BODY GENOME?????
// LINKS:::
for (int i = 0; i < genomeA.linkNEATList.Count + genomeB.linkNEATList.Count; i++)
{
if (indexA < genomeA.linkNEATList.Count)
{
if (indexB < genomeB.linkNEATList.Count) // both good
{
if (genomeA.linkNEATList[indexA].innov < genomeB.linkNEATList[indexB].innov)
{
// disjoint A
linkGenes++;
indexA++;
}
else if (genomeA.linkNEATList[indexA].innov > genomeB.linkNEATList[indexB].innov)
{
// disjoint B
linkGenes++;
indexB++;
}
else if (genomeA.linkNEATList[indexA].innov == genomeB.linkNEATList[indexB].innov)
{
// match!
float weightDelta = Mathf.Abs(genomeA.linkNEATList[indexA].weight - genomeB.linkNEATList[indexB].weight);
weightDeltaTotal += weightDelta;
matchingGenes++;
//Debug.Log("!@$#!$#!@$#!@$# MeasureGeneticDistance! innov MATCHING GENE: weightA: " + genomeA.linkNEATList[indexA].weight.ToString() + ", weightB: " + genomeB.linkNEATList[indexB].weight.ToString());
indexA++;
indexB++;
largestWeightDelta = Mathf.Max(largestWeightDelta, weightDelta);
}
}
else // A is good, B is finished
{
linkGenes++;
indexA++;
}
}
else // A done
{
if (indexB < genomeB.linkNEATList.Count) // A is finished, B is good
{
linkGenes++;
indexB++;
}
else // both done
{
break;
}
}
}
for (int i = 0; i < genomeA.nodeNEATList.Count; i++)
{
Int3 nodeID = new Int3(genomeA.nodeNEATList[i].sourceAddonInno, genomeA.nodeNEATList[i].sourceAddonRecursionNum, genomeA.nodeNEATList[i].sourceAddonChannelNum);
if (genomeB.GetNodeIndexFromInt3(nodeID) != -1) // if genomeB has the same neuron:
{
matchingNeurons++;
}
}
int totalNeurons = (genomeA.nodeNEATList.Count + genomeB.nodeNEATList.Count);
int totalLinks = (genomeA.linkNEATList.Count + genomeB.linkNEATList.Count);
if (totalNeurons > 0)
{
neuronGenes = Mathf.Lerp((float)((totalNeurons) - matchingNeurons * 2), (float)((totalNeurons) - matchingNeurons * 2) / (float)(totalNeurons), normNeuron); // get proportion of neurons that match between the two genomes, should be 0-1
}
if (totalLinks > 0)
{
linkGenes = Mathf.Lerp(((float)(totalLinks) - matchingGenes * 2f), ((float)(totalLinks) - matchingGenes * 2f) / (float)(totalLinks), normLink);
}
//float weightSpan = largestWeightValue - smallestWeightValue;
float distance = 0f;
if (true) // maxGenes > 0f
//float excessComponent = excessCoefficient * Mathf.Lerp(excessGenes, excessGenes / maxGenes, normExcess);
//float disjointComponent = disjointCoefficient * Mathf.Lerp(disjointGenes, disjointGenes / maxGenes, normDisjoint);
//float weightComponent = weightCoefficient * Mathf.Lerp(weightDeltaTotal, weightDeltaTotal / Mathf.Max((float)matchingGenes, 1f), normWeight);
{
float totalPie = neuronCoefficient + linkCoefficient + weightCoefficient;
float weightComponent = 0f;
if (largestWeightDelta > 0f)
{
weightComponent = Mathf.Lerp(weightDeltaTotal / largestWeightDelta, weightDeltaTotal / Mathf.Max((float)matchingGenes, 1f) / largestWeightDelta, normWeight);
}
// OLD //distance = excessComponent + disjointComponent + weightComponent;
distance = neuronGenes * (neuronCoefficient / totalPie) + linkGenes * (linkCoefficient / totalPie) + weightComponent * (weightCoefficient / totalPie);
//Debug.Log("MeasureGeneticDistance! neuronGenes: " + (neuronGenes).ToString() + " (" + genomeA.nodeNEATList.Count.ToString() + "," + genomeB.nodeNEATList.Count.ToString() +
// "), linkGenes: " + (linkGenes).ToString() + " (" + genomeA.linkNEATList.Count.ToString() + "," + genomeB.linkNEATList.Count.ToString() +
// "), weight: " + weightComponent.ToString() + ", largestWeightDelta: " + largestWeightDelta.ToString() + ", weightDeltaTotal: " + weightDeltaTotal.ToString() + "weightMatches: " + matchingGenes.ToString() +
// ", distance: " + distance.ToString());
//Debug.Log("MeasureGeneticDistance! disjoint: " + (disjointGenes).ToString() + ", excess: " + (excessGenes).ToString() + ", weight: " + (weightDeltaTotal / Mathf.Max((float)matchingGenes, 1f)).ToString() + ", distance: " + distance.ToString());
}
// else stays 0f;
return(distance);
}
public void PerformAddonMutation(ref CritterGenome bodyGenome, ref GenomeNEAT brainGenome) {
// Chance to Remove an existing Add-on:
// Chance to Mutate Add-On Settings:
for (int i = bodyGenome.addonPhysicalAttributesList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonPhysicalAttributesList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPhysicalAttributesList[i].bounciness[0] = MutateBodyFloatMult(bodyGenome.addonPhysicalAttributesList[i].bounciness[0], 0f, 1f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPhysicalAttributesList[i].dynamicFriction[0] = MutateBodyFloatMult(bodyGenome.addonPhysicalAttributesList[i].dynamicFriction[0], 0f, 1f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPhysicalAttributesList[i].staticFriction[0] = MutateBodyFloatMult(bodyGenome.addonPhysicalAttributesList[i].staticFriction[0], 0f, 1f);
}
/*if (CheckForMutation(addonSettingsChance)) {
bodyGenome.addonPhysicalAttributesList[i].freezePositionX[0] = MutateBodyBool(bodyGenome.addonPhysicalAttributesList[i].freezePositionX[0]);
}
if (CheckForMutation(addonSettingsChance)) {
bodyGenome.addonPhysicalAttributesList[i].freezePositionY[0] = MutateBodyBool(bodyGenome.addonPhysicalAttributesList[i].freezePositionY[0]);
}
if (CheckForMutation(addonSettingsChance)) {
bodyGenome.addonPhysicalAttributesList[i].freezePositionZ[0] = MutateBodyBool(bodyGenome.addonPhysicalAttributesList[i].freezePositionZ[0]);
}
if (CheckForMutation(addonSettingsChance)) {
bodyGenome.addonPhysicalAttributesList[i].freezeRotationX[0] = MutateBodyBool(bodyGenome.addonPhysicalAttributesList[i].freezeRotationX[0]);
}
if (CheckForMutation(addonSettingsChance)) {
bodyGenome.addonPhysicalAttributesList[i].freezeRotationY[0] = MutateBodyBool(bodyGenome.addonPhysicalAttributesList[i].freezeRotationY[0]);
}
if (CheckForMutation(addonSettingsChance)) {
bodyGenome.addonPhysicalAttributesList[i].freezeRotationZ[0] = MutateBodyBool(bodyGenome.addonPhysicalAttributesList[i].freezeRotationZ[0]);
}*/
}
}
for (int i = bodyGenome.addonJointAngleSensorList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonJointAngleSensorList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonJointAngleSensorList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonJointAngleSensorList[i].sensitivity[0], 0.001f, 100f);
}
// ################# How to handle MEasureVel Checkbox?? It adds a Neuron!!!!!!!!!
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
}
}
for (int i = bodyGenome.addonContactSensorList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonContactSensorList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonContactSensorList[i].contactSensitivity[0] = MutateBodyFloatMult(bodyGenome.addonContactSensorList[i].contactSensitivity[0], 0.01f, 10f);
}
}
}
for (int i = bodyGenome.addonRaycastSensorList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonRaycastSensorList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonRaycastSensorList[i].forwardVector[0] = MutateBodyVector3Normalized(bodyGenome.addonRaycastSensorList[i].forwardVector[0]);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonRaycastSensorList[i].maxDistance[0] = MutateBodyFloatMult(bodyGenome.addonRaycastSensorList[i].maxDistance[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonCompassSensor1DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonCompassSensor1DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonCompassSensor1DList[i].forwardVector[0] = MutateBodyVector3Normalized(bodyGenome.addonCompassSensor1DList[i].forwardVector[0]);
}
}
}
for (int i = bodyGenome.addonCompassSensor3DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonCompassSensor3DList.RemoveAt(i);
}
else {
}
}
for (int i = bodyGenome.addonPositionSensor1DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonPositionSensor1DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPositionSensor1DList[i].forwardVector[0] = MutateBodyVector3Normalized(bodyGenome.addonPositionSensor1DList[i].forwardVector[0]);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPositionSensor1DList[i].relative[0] = MutateBodyBool(bodyGenome.addonPositionSensor1DList[i].relative[0]);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPositionSensor1DList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonPositionSensor1DList[i].sensitivity[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonPositionSensor3DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonPositionSensor3DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPositionSensor3DList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonPositionSensor3DList[i].sensitivity[0], 0.01f, 100f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonPositionSensor3DList[i].relative[0] = MutateBodyBool(bodyGenome.addonPositionSensor3DList[i].relative[0]);
}
}
}
for (int i = bodyGenome.addonRotationSensor1DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonRotationSensor1DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonRotationSensor1DList[i].localAxis[0] = MutateBodyVector3Normalized(bodyGenome.addonRotationSensor1DList[i].localAxis[0]);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonRotationSensor1DList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonRotationSensor1DList[i].sensitivity[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonRotationSensor3DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonRotationSensor3DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonRotationSensor3DList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonRotationSensor3DList[i].sensitivity[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonVelocitySensor1DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonVelocitySensor1DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonVelocitySensor1DList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonVelocitySensor1DList[i].sensitivity[0], 0.01f, 100f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonVelocitySensor1DList[i].forwardVector[0] = MutateBodyVector3Normalized(bodyGenome.addonVelocitySensor1DList[i].forwardVector[0]);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonVelocitySensor1DList[i].relative[0] = MutateBodyBool(bodyGenome.addonVelocitySensor1DList[i].relative[0]);
}
}
}
for (int i = bodyGenome.addonVelocitySensor3DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonVelocitySensor3DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonVelocitySensor3DList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonVelocitySensor3DList[i].sensitivity[0], 0.01f, 100f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonVelocitySensor3DList[i].relative[0] = MutateBodyBool(bodyGenome.addonVelocitySensor3DList[i].relative[0]);
}
}
}
for (int i = bodyGenome.addonAltimeterList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonAltimeterList.RemoveAt(i);
}
else {
}
}
for (int i = bodyGenome.addonEarBasicList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonEarBasicList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonEarBasicList[i].sensitivity[0] = MutateBodyFloatMult(bodyGenome.addonEarBasicList[i].sensitivity[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonGravitySensorList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonGravitySensorList.RemoveAt(i);
}
else {
}
}
for (int i = bodyGenome.addonOscillatorInputList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonOscillatorInputList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonOscillatorInputList[i].amplitude[0] = MutateBodyFloatMult(bodyGenome.addonOscillatorInputList[i].amplitude[0], 0.01f, 100f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonOscillatorInputList[i].frequency[0] = MutateBodyFloatMult(bodyGenome.addonOscillatorInputList[i].frequency[0], 0.01f, 50f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonOscillatorInputList[i].offset[0] = MutateBodyFloatMult(bodyGenome.addonOscillatorInputList[i].offset[0], -50f, 50f);
}
}
}
for (int i = bodyGenome.addonValueInputList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonValueInputList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonValueInputList[i].value[0] = MutateBodyFloatMult(bodyGenome.addonValueInputList[i].value[0], -100f, 100f);
}
}
}
for (int i = bodyGenome.addonTimerInputList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonTimerInputList.RemoveAt(i);
}
else {
}
}
//======================= OUTPUTS ===================== OUTPUTS ======================= OUTPUTS =====================================================
for (int i = bodyGenome.addonJointMotorList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonJointMotorList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonJointMotorList[i].motorForce[0] = MutateBodyFloatMult(bodyGenome.addonJointMotorList[i].motorForce[0], 0.01f, 200f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonJointMotorList[i].motorSpeed[0] = MutateBodyFloatMult(bodyGenome.addonJointMotorList[i].motorSpeed[0], 0.01f, 200f);
}
}
}
for (int i = bodyGenome.addonThrusterEffector1DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonThrusterEffector1DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonThrusterEffector1DList[i].forwardVector[0] = MutateBodyVector3Normalized(bodyGenome.addonThrusterEffector1DList[i].forwardVector[0]);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonThrusterEffector1DList[i].maxForce[0] = MutateBodyFloatMult(bodyGenome.addonThrusterEffector1DList[i].maxForce[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonThrusterEffector3DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonThrusterEffector3DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonThrusterEffector3DList[i].maxForce[0] = MutateBodyFloatMult(bodyGenome.addonThrusterEffector3DList[i].maxForce[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonTorqueEffector1DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonTorqueEffector1DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonTorqueEffector1DList[i].maxTorque[0] = MutateBodyFloatMult(bodyGenome.addonTorqueEffector1DList[i].maxTorque[0], 0.01f, 100f);
}
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonTorqueEffector1DList[i].axis[0] = MutateBodyVector3Normalized(bodyGenome.addonTorqueEffector1DList[i].axis[0]);
}
}
}
for (int i = bodyGenome.addonTorqueEffector3DList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonTorqueEffector3DList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonTorqueEffector3DList[i].maxTorque[0] = MutateBodyFloatMult(bodyGenome.addonTorqueEffector3DList[i].maxTorque[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonMouthBasicList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonMouthBasicList.RemoveAt(i);
}
else {
}
}
for (int i = bodyGenome.addonNoiseMakerBasicList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonNoiseMakerBasicList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonNoiseMakerBasicList[i].amplitude[0] = MutateBodyFloatMult(bodyGenome.addonNoiseMakerBasicList[i].amplitude[0], 0.01f, 100f);
}
}
}
for (int i = bodyGenome.addonStickyList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonStickyList.RemoveAt(i);
}
else {
}
}
for (int i = bodyGenome.addonWeaponBasicList.Count - 1; i >= 0; i--) {
if (CheckForMutation(removeAddonChance * bodyMutationBlastModifier)) {
// DELETE THIS ADD-ON!!!
bodyGenome.addonWeaponBasicList.RemoveAt(i);
}
else {
if (CheckForMutation(addonSettingsChance * bodyMutationBlastModifier)) {
bodyGenome.addonWeaponBasicList[i].strength[0] = MutateBodyFloatMult(bodyGenome.addonWeaponBasicList[i].strength[0], 0.01f, 100f);
}
}
}
// UPDATE BRAIN/BODY:
brainGenome.AdjustBrainAfterBodyChange(ref bodyGenome);
}
public Population BreedPopulation(ref Population sourcePopulation, int currentGeneration) {
#region Pre-Crossover, Figuring out how many agents to breed etc.
int LifetimeGeneration = currentGeneration + sourcePopulation.trainingGenerations;
int totalNumWeightMutations = 0;
//float totalWeightChangeValue = 0f;
// go through species list and adjust fitness
List<SpeciesBreedingPool> childSpeciesPoolsList = new List<SpeciesBreedingPool>(); // will hold agents in an internal list to facilitate crossover
for (int s = 0; s < sourcePopulation.speciesBreedingPoolList.Count; s++) {
SpeciesBreedingPool newChildSpeciesPool = new SpeciesBreedingPool(sourcePopulation.speciesBreedingPoolList[s].templateGenome, sourcePopulation.speciesBreedingPoolList[s].speciesID); // create Breeding Pools
// copies the existing breeding pools but leaves their agentLists empty for future children
childSpeciesPoolsList.Add(newChildSpeciesPool); // Add to list of pools
}
sourcePopulation.RankAgentArray(); // based on modified species fitness score, so compensated for species sizes
Agent[] newAgentArray = new Agent[sourcePopulation.masterAgentArray.Length];
// Calculate total fitness score:
float totalScore = 0f;
if (survivalByRaffle) {
for (int a = 0; a < sourcePopulation.populationMaxSize; a++) { // iterate through all agents
totalScore += sourcePopulation.masterAgentArray[a].fitnessScoreSpecies;
}
}
// Figure out How many Agents survive
int numSurvivors = Mathf.RoundToInt(survivalRate * (float)sourcePopulation.populationMaxSize);
//Depending on method, one at a time, select an Agent to survive until the max Number is reached
int newChildIndex = 0;
// For ( num Agents ) {
for (int i = 0; i < numSurvivors; i++) {
// If survival is by fitness score ranking:
if (survivalByRank) {
// Pop should already be ranked, so just traverse from top (best) to bottom (worst)
newAgentArray[newChildIndex] = sourcePopulation.masterAgentArray[newChildIndex];
SpeciesBreedingPool survivingAgentBreedingPool = sourcePopulation.GetBreedingPoolByID(childSpeciesPoolsList, newAgentArray[newChildIndex].speciesID);
survivingAgentBreedingPool.AddNewAgent(newAgentArray[newChildIndex]);
//SortNewAgentIntoSpecies(newAgentArray[newChildIndex], childSpeciesList); // sorts this surviving agent into next generation's species'
newChildIndex++;
}
// if survival is completely random, as a control:
if (survivalStochastic) {
int randomAgent = UnityEngine.Random.Range(0, numSurvivors - 1);
// Set next newChild slot to a randomly-chosen agent within the survivor faction -- change to full random?
newAgentArray[newChildIndex] = sourcePopulation.masterAgentArray[randomAgent];
SpeciesBreedingPool survivingAgentBreedingPool = sourcePopulation.GetBreedingPoolByID(childSpeciesPoolsList, newAgentArray[newChildIndex].speciesID);
survivingAgentBreedingPool.AddNewAgent(newAgentArray[newChildIndex]);
//SortNewAgentIntoSpecies(newAgentArray[newChildIndex], childSpeciesList); // sorts this surviving agent into next generation's species'
newChildIndex++;
}
// if survival is based on a fitness lottery:
if (survivalByRaffle) { // Try when Fitness is normalized from 0-1
float randomSlicePosition = UnityEngine.Random.Range(0f, totalScore);
float accumulatedFitness = 0f;
for (int a = 0; a < sourcePopulation.populationMaxSize; a++) { // iterate through all agents
accumulatedFitness += sourcePopulation.masterAgentArray[a].fitnessScoreSpecies;
// if accum fitness is on slicePosition, copy this Agent
//Debug.Log("NumSurvivors: " + numSurvivors.ToString() + ", Surviving Agent " + a.ToString() + ": AccumFitness: " + accumulatedFitness.ToString() + ", RafflePos: " + randomSlicePosition.ToString() + ", TotalScore: " + totalScore.ToString() + ", newChildIndex: " + newChildIndex.ToString());
if (accumulatedFitness >= randomSlicePosition) {
newAgentArray[newChildIndex] = sourcePopulation.masterAgentArray[a]; // add to next gen's list of agents
SpeciesBreedingPool survivingAgentBreedingPool = sourcePopulation.GetBreedingPoolByID(childSpeciesPoolsList, newAgentArray[newChildIndex].speciesID);
survivingAgentBreedingPool.AddNewAgent(newAgentArray[newChildIndex]);
//SortNewAgentIntoSpecies(newAgentArray[newChildIndex], childSpeciesList); // sorts this surviving agent into next generation's species'
newChildIndex++;
break;
}
}
}
}
// Figure out how many new agents must be created to fill up the new population:
int numNewChildAgents = sourcePopulation.populationMaxSize - numSurvivors;
int numEligibleBreederAgents = Mathf.RoundToInt(breedingRate * (float)sourcePopulation.populationMaxSize);
int currentRankIndex = 0;
// Once the agents are ranked, trim the BreedingPools of agents that didn't make the cut for mating:
if(useSpeciation) {
for (int s = 0; s < sourcePopulation.speciesBreedingPoolList.Count; s++) {
int index = 0;
int failsafe = 0;
int numAgents = sourcePopulation.speciesBreedingPoolList[s].agentList.Count;
while (index < numAgents) {
if (index < sourcePopulation.speciesBreedingPoolList[s].agentList.Count) {
if (sourcePopulation.speciesBreedingPoolList[s].agentList[index].fitnessRank >= numEligibleBreederAgents) {
sourcePopulation.speciesBreedingPoolList[s].agentList.RemoveAt(index);
}
else {
index++;
}
}
else {
break;
}
failsafe++;
if (failsafe > 500) {
Debug.Log("INFINITE LOOP! hit failsafe 500 iters -- Trimming BreedingPools!");
break;
}
}
//Debug.Log("BreedPopulation -- TRIMSpeciesPool# " + s.ToString() + ", id: " + sourcePopulation.speciesBreedingPoolList[s].speciesID.ToString() + ", Count: " + sourcePopulation.speciesBreedingPoolList[s].agentList.Count.ToString());
//
}
}
float totalScoreBreeders = 0f;
if (breedingByRaffle) { // calculate total fitness scores to determine lottery weights
for (int a = 0; a < numEligibleBreederAgents; a++) { // iterate through all agents
totalScoreBreeders += sourcePopulation.masterAgentArray[a].fitnessScoreSpecies;
}
}
#endregion
// Iterate over numAgentsToCreate :
int newChildrenCreated = 0;
while (newChildrenCreated < numNewChildAgents) {
// Find how many parents random number btw min/max:
int numParentAgents = 2; // UnityEngine.Random.Range(minNumParents, maxNumParents);
int numChildAgents = 1; // defaults to one child, but:
if (numNewChildAgents - newChildrenCreated >= 2) { // room for two more!
numChildAgents = 2;
}
Agent[] parentAgentsArray = new Agent[numParentAgents]; // assume 2 for now? yes, so far....
List<GeneNodeNEAT>[] parentNodeListArray = new List<GeneNodeNEAT>[numParentAgents];
List<GeneLinkNEAT>[] parentLinkListArray = new List<GeneLinkNEAT>[numParentAgents];
Agent firstParentAgent = SelectAgentFromPopForBreeding(sourcePopulation, numEligibleBreederAgents, ref currentRankIndex);
parentAgentsArray[0] = firstParentAgent;
List<GeneNodeNEAT> firstParentNodeList = firstParentAgent.brainGenome.nodeNEATList;
List<GeneLinkNEAT> firstParentLinkList = firstParentAgent.brainGenome.linkNEATList;
//List<GeneNodeNEAT> firstParentNodeList = new List<GeneNodeNEAT>();
//List<GeneLinkNEAT> firstParentLinkList = new List<GeneLinkNEAT>();
//firstParentNodeList = firstParentAgent.brainGenome.nodeNEATList;
//firstParentLinkList = firstParentAgent.brainGenome.linkNEATList;
parentNodeListArray[0] = firstParentNodeList;
parentLinkListArray[0] = firstParentLinkList;
Agent secondParentAgent;
SpeciesBreedingPool parentAgentBreedingPool = sourcePopulation.GetBreedingPoolByID(sourcePopulation.speciesBreedingPoolList, firstParentAgent.speciesID);
if (useSpeciation) {
//parentAgentBreedingPool
float randBreedOutsideSpecies = UnityEngine.Random.Range(0f, 1f);
if (randBreedOutsideSpecies < interspeciesBreedingRate) { // Attempts to Found a new species
// allowed to breed outside its own species:
secondParentAgent = SelectAgentFromPopForBreeding(sourcePopulation, numEligibleBreederAgents, ref currentRankIndex);
}
else {
// Selects mate only from within its own species:
secondParentAgent = SelectAgentFromPoolForBreeding(parentAgentBreedingPool);
}
}
else {
secondParentAgent = SelectAgentFromPopForBreeding(sourcePopulation, numEligibleBreederAgents, ref currentRankIndex);
}
parentAgentsArray[1] = secondParentAgent;
List<GeneNodeNEAT> secondParentNodeList = secondParentAgent.brainGenome.nodeNEATList;
List<GeneLinkNEAT> secondParentLinkList = secondParentAgent.brainGenome.linkNEATList;
//List<GeneNodeNEAT> secondParentNodeList = new List<GeneNodeNEAT>();
//List<GeneLinkNEAT> secondParentLinkList = new List<GeneLinkNEAT>();
//secondParentNodeList = secondParentAgent.brainGenome.nodeNEATList;
//secondParentLinkList = secondParentAgent.brainGenome.linkNEATList;
parentNodeListArray[1] = secondParentNodeList;
parentLinkListArray[1] = secondParentLinkList;
// Iterate over ChildArray.Length : // how many newAgents created
for (int c = 0; c < numChildAgents; c++) { // for number of child Agents in floatArray[][]:
Agent newChildAgent = new Agent();
List<GeneNodeNEAT> childNodeList = new List<GeneNodeNEAT>();
List<GeneLinkNEAT> childLinkList = new List<GeneLinkNEAT>();
GenomeNEAT childBrainGenome = new GenomeNEAT();
childBrainGenome.nodeNEATList = childNodeList;
childBrainGenome.linkNEATList = childLinkList;
int numEnabledLinkGenes = 0;
if (useCrossover) {
int nextLinkInnoA = 0;
int nextLinkInnoB = 0;
//int nextBodyNodeInno = 0;
//int nextBodyAddonInno = 0;
int failsafeMax = 500;
int failsafe = 0;
int parentListIndexA = 0;
int parentListIndexB = 0;
//int parentBodyNodeIndex = 0;
bool parentDoneA = false;
bool parentDoneB = false;
bool endReached = false;
int moreFitParent = 0; // which parent is more Fit
if (parentAgentsArray[0].fitnessScoreSpecies < parentAgentsArray[1].fitnessScoreSpecies) {
moreFitParent = 1;
}
else if (parentAgentsArray[0].fitnessScoreSpecies == parentAgentsArray[1].fitnessScoreSpecies) {
moreFitParent = Mathf.RoundToInt(UnityEngine.Random.Range(0f, 1f));
}
// MATCH UP Links between both agents, if they have a gene with matching Inno#, then mixing can occur
while (!endReached) {
failsafe++;
if(failsafe > failsafeMax) {
Debug.Log("failsafe reached!");
break;
}
// inno# of next links:
if(parentLinkListArray[0].Count > parentListIndexA) {
nextLinkInnoA = parentLinkListArray[0][parentListIndexA].innov;
}
else {
parentDoneA = true;
}
if (parentLinkListArray[1].Count > parentListIndexB) {
nextLinkInnoB = parentLinkListArray[1][parentListIndexB].innov;
}
else {
parentDoneB = true;
}
int innoDelta = nextLinkInnoA - nextLinkInnoB; // 0=match, neg= Aextra, pos= Bextra
if (parentDoneA && !parentDoneB) {
innoDelta = 1;
}
if (parentDoneB && !parentDoneA) {
innoDelta = -1;
}
if (parentDoneA && parentDoneB) { // reached end of both parent's linkLists
endReached = true;
break;
}
if (innoDelta < 0) { // Parent A has an earlier link mutation
//Debug.Log("newChildIndex: " + newChildIndex.ToString() + ", IndexA: " + parentListIndexA.ToString() + ", IndexB: " + parentListIndexB.ToString() + ", innoDelta < 0 (" + innoDelta.ToString() + ") -- moreFitP: " + moreFitParent.ToString() + ", nextLinkInnoA: " + nextLinkInnoA.ToString() + ", nextLinkInnoB: " + nextLinkInnoB.ToString());
if (moreFitParent == 0) { // Parent A is more fit:
GeneLinkNEAT newChildLink = new GeneLinkNEAT(parentLinkListArray[0][parentListIndexA].fromNodeID, parentLinkListArray[0][parentListIndexA].toNodeID, parentLinkListArray[0][parentListIndexA].weight, parentLinkListArray[0][parentListIndexA].enabled, parentLinkListArray[0][parentListIndexA].innov, parentLinkListArray[0][parentListIndexA].birthGen);
childLinkList.Add(newChildLink);
if (parentLinkListArray[0][parentListIndexA].enabled)
numEnabledLinkGenes++;
}
else {
if(CheckForMutation(crossoverRandomLinkChance)) { // was less fit parent, but still passed on a gene!:
GeneLinkNEAT newChildLink = new GeneLinkNEAT(parentLinkListArray[0][parentListIndexA].fromNodeID, parentLinkListArray[0][parentListIndexA].toNodeID, parentLinkListArray[0][parentListIndexA].weight, parentLinkListArray[0][parentListIndexA].enabled, parentLinkListArray[0][parentListIndexA].innov, parentLinkListArray[0][parentListIndexA].birthGen);
childLinkList.Add(newChildLink);
}
}
parentListIndexA++;
}
if (innoDelta > 0) { // Parent B has an earlier link mutation
//Debug.Log("newChildIndex: " + newChildIndex.ToString() + ", IndexA: " + parentListIndexA.ToString() + ", IndexB: " + parentListIndexB.ToString() + ", innoDelta > 0 (" + innoDelta.ToString() + ") -- moreFitP: " + moreFitParent.ToString() + ", nextLinkInnoA: " + nextLinkInnoA.ToString() + ", nextLinkInnoB: " + nextLinkInnoB.ToString());
if (moreFitParent == 1) { // Parent B is more fit:
GeneLinkNEAT newChildLink = new GeneLinkNEAT(parentLinkListArray[1][parentListIndexB].fromNodeID, parentLinkListArray[1][parentListIndexB].toNodeID, parentLinkListArray[1][parentListIndexB].weight, parentLinkListArray[1][parentListIndexB].enabled, parentLinkListArray[1][parentListIndexB].innov, parentLinkListArray[1][parentListIndexB].birthGen);
childLinkList.Add(newChildLink);
if (parentLinkListArray[1][parentListIndexB].enabled)
numEnabledLinkGenes++;
}
else {
if (CheckForMutation(crossoverRandomLinkChance)) { // was less fit parent, but still passed on a gene!:
GeneLinkNEAT newChildLink = new GeneLinkNEAT(parentLinkListArray[1][parentListIndexB].fromNodeID, parentLinkListArray[1][parentListIndexB].toNodeID, parentLinkListArray[1][parentListIndexB].weight, parentLinkListArray[1][parentListIndexB].enabled, parentLinkListArray[1][parentListIndexB].innov, parentLinkListArray[1][parentListIndexB].birthGen);
childLinkList.Add(newChildLink);
}
}
parentListIndexB++;
}
if (innoDelta == 0) { // Match!
float randParentIndex = UnityEngine.Random.Range(0f, 1f);
float newWeightValue;
if (randParentIndex < 0.5) {
// ParentA wins:
newWeightValue = parentLinkListArray[0][parentListIndexA].weight;
}
else { // ParentB wins:
newWeightValue = parentLinkListArray[1][parentListIndexB].weight;
}
//Debug.Log("newChildIndex: " + newChildIndex.ToString() + ", IndexA: " + parentListIndexA.ToString() + ", IndexB: " + parentListIndexB.ToString() + ", innoDelta == 0 (" + innoDelta.ToString() + ") -- moreFitP: " + moreFitParent.ToString() + ", nextLinkInnoA: " + nextLinkInnoA.ToString() + ", nextLinkInnoB: " + nextLinkInnoB.ToString() + ", randParent: " + randParentIndex.ToString() + ", weight: " + newWeightValue.ToString());
GeneLinkNEAT newChildLink = new GeneLinkNEAT(parentLinkListArray[0][parentListIndexA].fromNodeID, parentLinkListArray[0][parentListIndexA].toNodeID, newWeightValue, parentLinkListArray[0][parentListIndexA].enabled, parentLinkListArray[0][parentListIndexA].innov, parentLinkListArray[0][parentListIndexA].birthGen);
childLinkList.Add(newChildLink);
if (parentLinkListArray[0][parentListIndexA].enabled)
numEnabledLinkGenes++;
parentListIndexA++;
parentListIndexB++;
}
}
// once childLinkList is built -- use nodes of the moreFit parent:
for (int i = 0; i < parentNodeListArray[moreFitParent].Count; i++) {
// iterate through all nodes in the parent List and copy them into fresh new geneNodes:
GeneNodeNEAT clonedNode = new GeneNodeNEAT(parentNodeListArray[moreFitParent][i].id, parentNodeListArray[moreFitParent][i].nodeType, parentNodeListArray[moreFitParent][i].activationFunction, parentNodeListArray[moreFitParent][i].sourceAddonInno, parentNodeListArray[moreFitParent][i].sourceAddonRecursionNum, false, parentNodeListArray[moreFitParent][i].sourceAddonChannelNum);
childNodeList.Add(clonedNode);
}
if (useMutation) {
// BODY MUTATION:
//PerformBodyMutation(ref childBodyGenome, ref childBrainGenome);
// NEED TO ADJUST BRAINS IF MUTATION CHANGES #NODES!!!!
// BRAIN MUTATION:
if (numEnabledLinkGenes < 1)
numEnabledLinkGenes = 1;
for (int k = 0; k < childLinkList.Count; k++) {
float mutateChance = mutationBlastModifier * masterMutationRate / (1f + (float)numEnabledLinkGenes * 0.15f);
if (LifetimeGeneration - childLinkList[k].birthGen < newLinkBonusDuration) {
float t = 1 - ((LifetimeGeneration - childLinkList[k].birthGen) / (float)newLinkBonusDuration);
// t=0 means age of gene is same as bonusDuration, t=1 means it is brand new
mutateChance = Mathf.Lerp(mutateChance, mutateChance * newLinkMutateBonus, t);
}
if (CheckForMutation(mutateChance)) { // Weight Mutation!
//Debug.Log("Weight Mutation Link[" + k.ToString() + "] weight: " + childLinkList[k].weight.ToString() + ", mutate: " + MutateFloat(childLinkList[k].weight).ToString());
childLinkList[k].weight = MutateFloat(childLinkList[k].weight);
totalNumWeightMutations++;
}
}
if (CheckForMutation(mutationBlastModifier * mutationRemoveLinkChance)) {
//Debug.Log("Remove Link Mutation Agent[" + newChildIndex.ToString() + "]");
childBrainGenome.RemoveRandomLink();
}
if (CheckForMutation(mutationBlastModifier * mutationAddNodeChance)) { // Adds a new node
//Debug.Log("Add Node Mutation Agent[" + newChildIndex.ToString() + "]");
childBrainGenome.AddNewRandomNode(LifetimeGeneration, GetNextAddonInnov());
}
if (CheckForMutation(mutationBlastModifier * mutationRemoveNodeChance)) { // Adds a new node
//Debug.Log("Add Node Mutation Agent[" + newChildIndex.ToString() + "]");
childBrainGenome.RemoveRandomNode();
}
if (CheckForMutation(mutationBlastModifier * mutationAddLinkChance)) { // Adds new connection
//Debug.Log("Add Link Mutation Agent[" + newChildIndex.ToString() + "]");
if (CheckForMutation(existingNetworkBias)) {
childBrainGenome.AddNewExtraLink(existingFromNodeBias, LifetimeGeneration);
}
else {
childBrainGenome.AddNewRandomLink(LifetimeGeneration);
}
}
if (CheckForMutation(mutationBlastModifier * mutationActivationFunctionChance)) {
TransferFunctions.TransferFunction newFunction;
int randIndex = Mathf.RoundToInt(UnityEngine.Random.Range(0f, childNodeList.Count - 1));
int randomTF = (int)UnityEngine.Random.Range(0f, 12f);
switch (randomTF) {
case 0:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
case 1:
newFunction = TransferFunctions.TransferFunction.Linear;
break;
case 2:
newFunction = TransferFunctions.TransferFunction.Gaussian;
break;
case 3:
newFunction = TransferFunctions.TransferFunction.Abs;
break;
case 4:
newFunction = TransferFunctions.TransferFunction.Cos;
break;
case 5:
newFunction = TransferFunctions.TransferFunction.Sin;
break;
case 6:
newFunction = TransferFunctions.TransferFunction.Tan;
break;
case 7:
newFunction = TransferFunctions.TransferFunction.Square;
break;
case 8:
newFunction = TransferFunctions.TransferFunction.Threshold01;
break;
case 9:
newFunction = TransferFunctions.TransferFunction.ThresholdNegPos;
break;
case 10:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
case 11:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
case 12:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
default:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
}
if (childNodeList[randIndex].nodeType != GeneNodeNEAT.GeneNodeType.Out) { // keep outputs -1 to 1 range
Debug.Log("ActivationFunction Mutation Node[" + randIndex.ToString() + "] prev: " + childNodeList[randIndex].activationFunction.ToString() + ", new: " + newFunction.ToString());
childNodeList[randIndex].activationFunction = newFunction;
}
}
}
else {
Debug.Log("Mutation Disabled!");
}
// THE BODY ==========!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!======================================================================================
CritterGenome childBodyGenome = new CritterGenome(); // create new body genome for Child
// This creates the ROOT NODE!!!!
// Clone Nodes & Addons from more fit parent to create new child body genome
// crossover is on, so check for matching Nodes and Add-ons (based on Inno#'s) to determine when to mix Settings/Attributes:
// Iterate over the nodes of the more fit parent:
for (int i = 0; i < parentAgentsArray[moreFitParent].bodyGenome.CritterNodeList.Count; i++) {
int currentNodeInno = parentAgentsArray[moreFitParent].bodyGenome.CritterNodeList[i].innov;
if (i == 0) { // if this is the ROOT NODE:
childBodyGenome.CritterNodeList[0].CopySettingsFromNode(parentAgentsArray[moreFitParent].bodyGenome.CritterNodeList[0]);
// The root node was already created during the Constructor method of the CritterGenome,
// ... so instead of creating a new one, just copy the settings
}
else { // NOT the root node, proceed normally:
// Create new cloned node defaulted to the settings of the source( more-fit parent's) Node:
CritterNode clonedCritterNode = parentAgentsArray[moreFitParent].bodyGenome.CritterNodeList[i].CloneThisCritterNode();
// Check other parent for same node:
for (int j = 0; j < parentAgentsArray[1 - moreFitParent].bodyGenome.CritterNodeList.Count; j++) {
if (parentAgentsArray[1 - moreFitParent].bodyGenome.CritterNodeList[j].innov == currentNodeInno) {
// CROSSOVER NODE SETTINGS HERE!!! ---- If random dice roll > 0.5, use less fit parent's settings, otherwise leave as default
BodyCrossover(ref clonedCritterNode, parentAgentsArray[1 - moreFitParent].bodyGenome.CritterNodeList[j]);
}
}
childBodyGenome.CritterNodeList.Add(clonedCritterNode);
}
}
// ADD-ONS!!!!!!!!!!!!!!!!!!!!!!
BreedCritterAddons(ref childBodyGenome, ref parentAgentsArray[moreFitParent].bodyGenome, ref parentAgentsArray[1 - moreFitParent].bodyGenome);
newChildAgent.bodyGenome = childBodyGenome; // ?????
if (useMutation) {
// BODY MUTATION:
PerformBodyMutation(ref childBodyGenome, ref childBrainGenome);
}
}
else { // no crossover:
//===============================================================================================
for (int i = 0; i < parentNodeListArray[0].Count; i++) {
// iterate through all nodes in the parent List and copy them into fresh new geneNodes:
GeneNodeNEAT clonedNode = new GeneNodeNEAT(parentNodeListArray[0][i].id, parentNodeListArray[0][i].nodeType, parentNodeListArray[0][i].activationFunction, parentNodeListArray[0][i].sourceAddonInno, parentNodeListArray[0][i].sourceAddonRecursionNum, false, parentNodeListArray[0][i].sourceAddonChannelNum);
childNodeList.Add(clonedNode);
}
for (int j = 0; j < parentLinkListArray[0].Count; j++) {
//same thing with connections
GeneLinkNEAT clonedLink = new GeneLinkNEAT(parentLinkListArray[0][j].fromNodeID, parentLinkListArray[0][j].toNodeID, parentLinkListArray[0][j].weight, parentLinkListArray[0][j].enabled, parentLinkListArray[0][j].innov, parentLinkListArray[0][j].birthGen);
childLinkList.Add(clonedLink);
if (parentLinkListArray[0][j].enabled)
numEnabledLinkGenes++;
}
// MUTATION:
if (useMutation) {
// BODY MUTATION:
//childBrainGenome.nodeNEATList = childNodeList
//PerformBodyMutation(ref childBodyGenome, ref childBrainGenome);
// BRAIN MUTATION:
if (numEnabledLinkGenes < 1)
numEnabledLinkGenes = 1;
for (int k = 0; k < childLinkList.Count; k++) {
float mutateChance = mutationBlastModifier * masterMutationRate / (1f + (float)numEnabledLinkGenes * 0.15f);
if (LifetimeGeneration - childLinkList[k].birthGen < newLinkBonusDuration) {
float t = 1 - ((LifetimeGeneration - childLinkList[k].birthGen) / (float)newLinkBonusDuration);
// t=0 means age of gene is same as bonusDuration, t=1 means it is brand new
mutateChance = Mathf.Lerp(mutateChance, mutateChance * newLinkMutateBonus, t);
}
if (CheckForMutation(mutateChance)) { // Weight Mutation!
//Debug.Log("Weight Mutation Link[" + k.ToString() + "] weight: " + childLinkList[k].weight.ToString() + ", mutate: " + MutateFloat(childLinkList[k].weight).ToString());
childLinkList[k].weight = MutateFloat(childLinkList[k].weight);
totalNumWeightMutations++;
}
}
if (CheckForMutation(mutationBlastModifier * mutationRemoveLinkChance)) {
//Debug.Log("Remove Link Mutation Agent[" + newChildIndex.ToString() + "]");
childBrainGenome.RemoveRandomLink();
}
if (CheckForMutation(mutationBlastModifier * mutationAddNodeChance)) { // Adds a new node
//Debug.Log("Add Node Mutation Agent[" + newChildIndex.ToString() + "]");
childBrainGenome.AddNewRandomNode(LifetimeGeneration, GetNextAddonInnov());
}
if (CheckForMutation(mutationBlastModifier * mutationAddLinkChance)) { // Adds new connection
//Debug.Log("Add Link Mutation Agent[" + newChildIndex.ToString() + "]");
if(CheckForMutation(existingNetworkBias)) {
childBrainGenome.AddNewExtraLink(existingFromNodeBias, LifetimeGeneration);
}
else {
childBrainGenome.AddNewRandomLink(LifetimeGeneration);
}
}
if (CheckForMutation(mutationBlastModifier * mutationActivationFunctionChance)) {
TransferFunctions.TransferFunction newFunction;
int randIndex = Mathf.RoundToInt(UnityEngine.Random.Range(0f, childNodeList.Count - 1));
int randomTF = (int)UnityEngine.Random.Range(0f, 12f);
switch (randomTF) {
case 0:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
case 1:
newFunction = TransferFunctions.TransferFunction.Linear;
break;
case 2:
newFunction = TransferFunctions.TransferFunction.Gaussian;
break;
case 3:
newFunction = TransferFunctions.TransferFunction.Abs;
break;
case 4:
newFunction = TransferFunctions.TransferFunction.Cos;
break;
case 5:
newFunction = TransferFunctions.TransferFunction.Sin;
break;
case 6:
newFunction = TransferFunctions.TransferFunction.Tan;
break;
case 7:
newFunction = TransferFunctions.TransferFunction.Square;
break;
case 8:
newFunction = TransferFunctions.TransferFunction.Threshold01;
break;
case 9:
newFunction = TransferFunctions.TransferFunction.ThresholdNegPos;
break;
case 10:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
case 11:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
case 12:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
default:
newFunction = TransferFunctions.TransferFunction.RationalSigmoid;
break;
}
if (childNodeList[randIndex].nodeType != GeneNodeNEAT.GeneNodeType.Out) { // keep outputs -1 to 1 range
Debug.Log("ActivationFunction Mutation Node[" + randIndex.ToString() + "] prev: " + childNodeList[randIndex].activationFunction.ToString() + ", new: " + newFunction.ToString());
childNodeList[randIndex].activationFunction = newFunction;
}
}
//for (int t = 0; t < childNodeList.Count; t++) {
//}
}
else {
Debug.Log("Mutation Disabled!");
}
// THE BODY!!!!! ++++++++++++++++++++++================+++++++++++++++++++===============+++++++++++++++++++===================+++++++++++++++++==============
CritterGenome childBodyGenome = new CritterGenome(); // create new body genome for Child
// Iterate over the nodes of the more fit parent:
for (int i = 0; i < parentAgentsArray[0].bodyGenome.CritterNodeList.Count; i++) {
int currentNodeInno = parentAgentsArray[0].bodyGenome.CritterNodeList[i].innov;
if (i == 0) { // if this is the ROOT NODE:
childBodyGenome.CritterNodeList[0].CopySettingsFromNode(parentAgentsArray[0].bodyGenome.CritterNodeList[0]);
// The root node was already created during the Constructor method of the CritterGenome,
// ... so instead of creating a new one, just copy the settings
}
else { // NOT the root node, proceed normally:
// Create new cloned node defaulted to the settings of the source( more-fit parent's) Node:
CritterNode clonedCritterNode = parentAgentsArray[0].bodyGenome.CritterNodeList[i].CloneThisCritterNode();
childBodyGenome.CritterNodeList.Add(clonedCritterNode);
}
}
// ADD-ONS!!!!!!!!!!!!!!!!!!!!!!
BreedCritterAddons(ref childBodyGenome, ref parentAgentsArray[0].bodyGenome, ref parentAgentsArray[0].bodyGenome);
newChildAgent.bodyGenome = childBodyGenome;
if (useMutation) {
// BODY MUTATION:
PerformBodyMutation(ref childBodyGenome, ref childBrainGenome);
}
}
newChildAgent.brainGenome = childBrainGenome;
//newChildAgent.brainGenome.nodeNEATList = childNodeList;
//newChildAgent.brainGenome.linkNEATList = childLinkList;
BrainNEAT childBrain = new BrainNEAT(newChildAgent.brainGenome);
childBrain.BuildBrainNetwork();
newChildAgent.brain = childBrain;
//Debug.Log("NEW CHILD numNodes: " + newChildAgent.brainGenome.nodeNEATList.Count.ToString() + ", #Neurons: " + newChildAgent.brain.neuronList.Count.ToString());
//newChildAgent.bodyGenome.PreBuildCritter(0.8f);
// Species:
if (useSpeciation) {
float randAdoption = UnityEngine.Random.Range(0f, 1f);
if (randAdoption < adoptionRate) { // Attempts to Found a new species
bool speciesGenomeMatch = false;
for (int s = 0; s < childSpeciesPoolsList.Count; s++) {
float geneticDistance = GenomeNEAT.MeasureGeneticDistance(newChildAgent.brainGenome, childSpeciesPoolsList[s].templateGenome, neuronWeight, linkWeight, weightWeight, normalizeExcess, normalizeDisjoint, normalizeLinkWeight);
if (geneticDistance < speciesSimilarityThreshold) {
speciesGenomeMatch = true;
//agent.speciesID = speciesBreedingPoolList[s].speciesID; // this is done inside the AddNewAgent method below v v v
childSpeciesPoolsList[s].AddNewAgent(newChildAgent);
//Debug.Log(" NEW CHILD (" + newChildIndex.ToString() + ") SortAgentIntoBreedingPool dist: " + geneticDistance.ToString() + ", speciesIDs: " + newChildAgent.speciesID.ToString() + ", " + childSpeciesPoolsList[s].speciesID.ToString() + ", speciesCount: " + childSpeciesPoolsList[s].agentList.Count.ToString());
break;
}
}
if (!speciesGenomeMatch) {
SpeciesBreedingPool newSpeciesBreedingPool = new SpeciesBreedingPool(newChildAgent.brainGenome, sourcePopulation.GetNextSpeciesID()); // creates new speciesPool modeled on this agent's genome
newSpeciesBreedingPool.AddNewAgent(newChildAgent); // add this agent to breeding pool
childSpeciesPoolsList.Add(newSpeciesBreedingPool); // add new speciesPool to the population's list of all active species
//Debug.Log(" NEW CHILD (" + newChildIndex.ToString() + ") SortAgentIntoBreedingPool NO MATCH!!! -- creating new BreedingPool " + newSpeciesBreedingPool.speciesID.ToString() + ", newChildAgentSpeciesID: " + newChildAgent.speciesID.ToString());
}
}
else { // joins parent species automatically:
SpeciesBreedingPool newSpeciesBreedingPool = sourcePopulation.GetBreedingPoolByID(childSpeciesPoolsList, parentAgentBreedingPool.speciesID);
newSpeciesBreedingPool.AddNewAgent(newChildAgent); // add this agent to breeding pool
//Debug.Log(" NEW CHILD (" + newChildIndex.ToString() + ") NO ADOPTION SortAgentIntoBreedingPool speciesIDs: " + newChildAgent.speciesID.ToString() + ", " + newSpeciesBreedingPool.speciesID.ToString() + ", speciesCount: " + newSpeciesBreedingPool.agentList.Count.ToString());
}
}
else { // joins parent species automatically:
SpeciesBreedingPool newSpeciesBreedingPool = sourcePopulation.GetBreedingPoolByID(childSpeciesPoolsList, parentAgentBreedingPool.speciesID);
newSpeciesBreedingPool.AddNewAgent(newChildAgent); // add this agent to breeding pool
}
newChildAgent.parentFitnessScoreA = sourcePopulation.masterAgentArray[newChildIndex].fitnessScore;
newAgentArray[newChildIndex] = newChildAgent;
newChildIndex++; // new child created!
newChildrenCreated++;
}
}
/*Debug.Log("Finished Crossover! childSpeciesPoolsList:");
for (int i = 0; i < sourcePopulation.speciesBreedingPoolList.Count; i++) {
string poolString = " Child Species ID: " + sourcePopulation.speciesBreedingPoolList[i].speciesID.ToString();
for (int j = 0; j < sourcePopulation.speciesBreedingPoolList[i].agentList.Count; j++) {
poolString += ", member# " + j.ToString() + ", species: " + sourcePopulation.speciesBreedingPoolList[i].agentList[j].speciesID.ToString() + ", fitRank: " + sourcePopulation.speciesBreedingPoolList[i].agentList[j].fitnessRank.ToString();
}
Debug.Log(poolString);
}*/
// Clear out extinct species:
int listIndex = 0;
for (int s = 0; s < childSpeciesPoolsList.Count; s++) {
if (listIndex >= childSpeciesPoolsList.Count) {
Debug.Log("end childSpeciesPoolsList " + childSpeciesPoolsList.Count.ToString() + ", index= " + listIndex.ToString());
break;
}
else {
if (childSpeciesPoolsList[listIndex].agentList.Count == 0) { // if empty:
//Debug.Log("Species " + childSpeciesPoolsList[listIndex].speciesID.ToString() + " WENT EXTINCT!!! --- childSpeciesPoolsList[" + listIndex.ToString() + "] old Count: " + childSpeciesPoolsList.Count.ToString() + ", s: " + s.ToString());
childSpeciesPoolsList.RemoveAt(listIndex);
//s--; // see if this works
}
else {
listIndex++;
}
}
}
Debug.Log("Finished Crossover! totalNumWeightMutations: " + totalNumWeightMutations.ToString() + ", mutationBlastModifier: " + mutationBlastModifier.ToString() + ", bodyMutationBlastModifier: " + bodyMutationBlastModifier.ToString() + ", LifetimeGeneration: " + LifetimeGeneration.ToString() + ", currentGeneration: " + currentGeneration.ToString() + ", sourcePopulation.trainingGenerations: " + sourcePopulation.trainingGenerations.ToString());
sourcePopulation.masterAgentArray = newAgentArray;
sourcePopulation.speciesBreedingPoolList = childSpeciesPoolsList;
/*Debug.Log("Finished Crossover! sourcePopulation.speciesBreedingPoolList:");
for (int i = 0; i < sourcePopulation.speciesBreedingPoolList.Count; i++) {
string poolString = "New Species ID: " + sourcePopulation.speciesBreedingPoolList[i].speciesID.ToString();
for (int j = 0; j < sourcePopulation.speciesBreedingPoolList[i].agentList.Count; j++) {
poolString += ", member# " + j.ToString() + ", species: " + sourcePopulation.speciesBreedingPoolList[i].agentList[j].speciesID.ToString() + ", fitRank: " + sourcePopulation.speciesBreedingPoolList[i].agentList[j].fitnessRank.ToString();
}
Debug.Log(poolString);
}*/
return sourcePopulation;
}
public BrainNEAT(GenomeNEAT newGenome) {
sourceGenome = newGenome;
visitedNodes = new List<NeuronNEAT>();
completedNodes = new List<NeuronNEAT>();
}
public void InitializeBrainFromGenome(GenomeNEAT newGenome) {
sourceGenome = newGenome;
}
public GenomeNEAT InitializeBlankBrain(int numInputNodes, int numOutputNodes) {
sourceGenome = new GenomeNEAT(numInputNodes, numOutputNodes); // create blank genome with no connections
/*int numNewLinks = 0;
int numNewNodes = 0;
for(int i = 0; i < numNewLinks; i++) {
sourceGenome.AddNewRandomLink(0);
}
for (int j = 0; j < numNewNodes; j++) {
sourceGenome.AddNewRandomNode(0);
}*/
//Debug.Log("InitializeBlankBrain #nodes: " + sourceGenome.nodeNEATList.Count.ToString() + ", #links: " + sourceGenome.linkNEATList.Count.ToString());
return sourceGenome;
}
public GenomeNEAT InitializeNewBrain(CritterGenome critterBodyGenome, int numHiddenNodes, float connectedness, bool randomWeights) {
// OLD //sourceGenome = new GenomeNEAT(numInputNodes, numHiddenNodes, numOutputNodes); // create blank genome with no connections
sourceGenome = new GenomeNEAT(critterBodyGenome, numHiddenNodes); // create blank genome with no connections
sourceGenome.CreateInitialConnections(connectedness, randomWeights);
//Debug.Log("InitializeBlankBrain #nodes: " + sourceGenome.nodeNEATList.Count.ToString() + ", #links: " + sourceGenome.linkNEATList.Count.ToString());
return sourceGenome;
}
public void InitializeBrainFromGenome(GenomeNEAT newGenome)
{
sourceGenome = newGenome;
}
public GenomeNEAT InitializeRandomBrain(int numInputNodes, int numOutputNodes) {
sourceGenome = new GenomeNEAT(numInputNodes, numOutputNodes); // create blank genome with no connections
sourceGenome.CreateMinimumRandomConnections(); // Add links to each output node froma random input node
return sourceGenome;
}
public BrainNEAT(GenomeNEAT newGenome)
{
sourceGenome = newGenome;
visitedNodes = new List <NeuronNEAT>();
completedNodes = new List <NeuronNEAT>();
}
public void ApplyTrainingModifierEffects(Trainer trainer)
{
int currentGen = trainer.PlayingCurGeneration;
if (trainer.loadedTrainingSave != null)
{
currentGen += trainer.loadedTrainingSave.endGeneration;
}
//Debug.Log("ApplyTrainingModifierEffects currentGen: " + currentGen.ToString());
CrossoverManager crossoverManager = trainer.PlayerList[0].masterCupid;
int numModifiers = activeTrainingModifierList.Count;
crossoverManager.mutationBlastModifier = 1f;
crossoverManager.bodyMutationBlastModifier = 1f;
if (numModifiers > 0)
{
for (int i = numModifiers - 1; i >= 0; i--)
{
float t = 0f;
switch (activeTrainingModifierList[i].modifierType)
{
case TrainingModifier.TrainingModifierType.LinkExplosion:
// go through all agents and pump them up -- THIS WILL NEED IMPROVEMENTS!!!!
for (int a = 0; a < trainer.PlayerList[0].masterPopulation.masterAgentArray.Length; a++)
{
GenomeNEAT genome = trainer.PlayerList[0].masterPopulation.masterAgentArray[a].brainGenome;
int numNodes = genome.nodeNEATList.Count;
int numNewLinks = (int)((float)numNodes * activeTrainingModifierList[i].linksPerNode);
for (int n = 0; n < numNewLinks; n++)
{
genome.AddNewRandomLink(currentGen);
}
int numLinks = genome.linkNEATList.Count;
int numNewNodes = (int)((float)numLinks * activeTrainingModifierList[i].nodesPerLink);
for (int b = 0; b < numNewNodes; b++)
{
genome.AddNewRandomNode(currentGen, crossoverManager.GetNextAddonInnov());
}
}
activeTrainingModifierList.RemoveAt(i);
break;
case TrainingModifier.TrainingModifierType.MutationBlast:
t = ((float)currentGen - (float)activeTrainingModifierList[i].startGen) / (float)activeTrainingModifierList[i].duration;
crossoverManager = trainer.PlayerList[0].masterCupid;
if (t > 1f)
{
if (activeTrainingModifierList[i].liveForever)
{
t = 1f;
}
else
{
// Duration has expired, and the live forever flag if false, so remove this modifier
crossoverManager.mutationBlastModifier = 1f;
activeTrainingModifierList.RemoveAt(i);
break;
}
}
crossoverManager.mutationBlastModifier = Mathf.Lerp(1f, activeTrainingModifierList[i].minMultiplier, t);
break;
case TrainingModifier.TrainingModifierType.BodyMutationBlast:
t = ((float)currentGen - (float)activeTrainingModifierList[i].startGen) / (float)activeTrainingModifierList[i].duration;
crossoverManager = trainer.PlayerList[0].masterCupid;
if (t > 1f)
{
if (activeTrainingModifierList[i].liveForever)
{
t = 1f;
}
else
{
// Duration has expired, and the live forever flag if false, so remove this modifier
crossoverManager.bodyMutationBlastModifier = 1f;
activeTrainingModifierList.RemoveAt(i);
break;
}
}
crossoverManager.bodyMutationBlastModifier = Mathf.Lerp(1f, activeTrainingModifierList[i].minMultiplier, t);
break;
case TrainingModifier.TrainingModifierType.PruneBrain:
t = ((float)currentGen - (float)activeTrainingModifierList[i].startGen) / (float)activeTrainingModifierList[i].duration;
crossoverManager = trainer.PlayerList[0].masterCupid;
if (t > 1f)
{
t = 1f;
}
t = 1f - t;
crossoverManager.largeBrainPenalty = activeTrainingModifierList[i].largeBrainPenalty * t;
crossoverManager.mutationRemoveLinkChance = activeTrainingModifierList[i].removeLinkChance * t;
crossoverManager.mutationRemoveNodeChance = activeTrainingModifierList[i].removeNodeChance * t;
break;
case TrainingModifier.TrainingModifierType.TargetCone:
break;
case TrainingModifier.TrainingModifierType.TargetForward:
break;
case TrainingModifier.TrainingModifierType.TargetOmni:
break;
case TrainingModifier.TrainingModifierType.VariableTrialTimes:
t = ((float)currentGen - (float)activeTrainingModifierList[i].startGen) / (float)activeTrainingModifierList[i].duration;
Trial trial = trainer.PlayerList[0].masterTrialsList[0];
if (t > 1f)
{
if (activeTrainingModifierList[i].liveForever)
{
t = 1f;
}
else
{
// Remove this modifier
activeTrainingModifierList.RemoveAt(i);
}
}
int minSteps = (int)Mathf.Lerp(activeTrainingModifierList[i].beginMinTime, activeTrainingModifierList[i].endMinTime, t);
int maxSteps = (int)Mathf.Lerp(activeTrainingModifierList[i].beginMaxTime, activeTrainingModifierList[i].endMaxTime, t);
trial.maxEvaluationTimeSteps = maxSteps; // (int)UnityEngine.Random.Range(minSteps, maxSteps);
trial.minEvaluationTimeSteps = minSteps;
break;
case TrainingModifier.TrainingModifierType.WideSearch:
t = ((float)currentGen - (float)activeTrainingModifierList[i].startGen) / (float)activeTrainingModifierList[i].duration;
crossoverManager = trainer.PlayerList[0].masterCupid;
if (t > 1f)
{
t = 1f;
}
t = 1f - t;
//crossoverManager.largeBrainPenalty = activeTrainingModifierList[i].largeBrainPenalty * t;
//crossoverManager.mutationRemoveLinkChance = activeTrainingModifierList[i].removeLinkChance * t;
//crossoverManager.mutationRemoveNodeChance = activeTrainingModifierList[i].removeNodeChance * t;
break;
default:
Debug.Log("Modifier type not found!!! SWITCH DEFAULT CASE");
break;
}
}
}
}
public SpeciesBreedingPool(GenomeNEAT genome, int id) {
agentList = new List<Agent>();
templateGenome = genome;
speciesID = id;
nextAgentIndex = 0;
}
public static float MeasureGeneticDistance(GenomeNEAT genomeA, GenomeNEAT genomeB, float neuronCoefficient, float linkCoefficient, float weightCoefficient, float normNeuron, float normLink, float normWeight) {
int indexA = 0;
int indexB = 0;
float weightDeltaTotal = 0f;
float maxGenes = Mathf.Max((float)genomeA.linkNEATList.Count, (float)genomeB.linkNEATList.Count);
float matchingGenes = 0f;
//float disjointGenes = 0f;
//float excessGenes = 0f;
float linkGenes = 0f;
float neuronGenes = 0f;
int matchingNeurons = 0;
//float smallestWeightValue = 0f;
float largestWeightDelta = 0f;
// matching Links
// matching nodes/neurons
// matching activation functions?
// difference in weights
// difference in add-on settings?
// -- NEED TO GO BY BODY GENOME?????
// LINKS:::
for(int i = 0; i < genomeA.linkNEATList.Count + genomeB.linkNEATList.Count; i++) {
if(indexA < genomeA.linkNEATList.Count) {
if (indexB < genomeB.linkNEATList.Count) { // both good
if (genomeA.linkNEATList[indexA].innov < genomeB.linkNEATList[indexB].innov) {
// disjoint A
linkGenes++;
indexA++;
}
else if (genomeA.linkNEATList[indexA].innov > genomeB.linkNEATList[indexB].innov) {
// disjoint B
linkGenes++;
indexB++;
}
else if (genomeA.linkNEATList[indexA].innov == genomeB.linkNEATList[indexB].innov) {
// match!
float weightDelta = Mathf.Abs(genomeA.linkNEATList[indexA].weight - genomeB.linkNEATList[indexB].weight);
weightDeltaTotal += weightDelta;
matchingGenes++;
//Debug.Log("!@$#!$#!@$#!@$# MeasureGeneticDistance! innov MATCHING GENE: weightA: " + genomeA.linkNEATList[indexA].weight.ToString() + ", weightB: " + genomeB.linkNEATList[indexB].weight.ToString());
indexA++;
indexB++;
largestWeightDelta = Mathf.Max(largestWeightDelta, weightDelta);
}
}
else { // A is good, B is finished
linkGenes++;
indexA++;
}
}
else { // A done
if (indexB < genomeB.linkNEATList.Count) { // A is finished, B is good
linkGenes++;
indexB++;
}
else { // both done
break;
}
}
}
for (int i = 0; i < genomeA.nodeNEATList.Count; i++) {
Int3 nodeID = new Int3(genomeA.nodeNEATList[i].sourceAddonInno, genomeA.nodeNEATList[i].sourceAddonRecursionNum, genomeA.nodeNEATList[i].sourceAddonChannelNum);
if(genomeB.GetNodeIndexFromInt3(nodeID) != -1) { // if genomeB has the same neuron:
matchingNeurons++;
}
}
int totalNeurons = (genomeA.nodeNEATList.Count + genomeB.nodeNEATList.Count);
int totalLinks = (genomeA.linkNEATList.Count + genomeB.linkNEATList.Count);
if(totalNeurons > 0) {
neuronGenes = Mathf.Lerp((float)((totalNeurons) - matchingNeurons * 2), (float)((totalNeurons) - matchingNeurons * 2) / (float)(totalNeurons), normNeuron); // get proportion of neurons that match between the two genomes, should be 0-1
}
if(totalLinks > 0) {
linkGenes = Mathf.Lerp(((float)(totalLinks) - matchingGenes * 2f), ((float)(totalLinks) - matchingGenes * 2f) / (float)(totalLinks), normLink);
}
//float weightSpan = largestWeightValue - smallestWeightValue;
float distance = 0f;
if(true) { // maxGenes > 0f
//float excessComponent = excessCoefficient * Mathf.Lerp(excessGenes, excessGenes / maxGenes, normExcess);
//float disjointComponent = disjointCoefficient * Mathf.Lerp(disjointGenes, disjointGenes / maxGenes, normDisjoint);
//float weightComponent = weightCoefficient * Mathf.Lerp(weightDeltaTotal, weightDeltaTotal / Mathf.Max((float)matchingGenes, 1f), normWeight);
float totalPie = neuronCoefficient + linkCoefficient + weightCoefficient;
float weightComponent = 0f;
if(largestWeightDelta > 0f)
weightComponent = Mathf.Lerp(weightDeltaTotal / largestWeightDelta, weightDeltaTotal / Mathf.Max((float)matchingGenes, 1f) / largestWeightDelta, normWeight);
// OLD //distance = excessComponent + disjointComponent + weightComponent;
distance = neuronGenes * (neuronCoefficient / totalPie) + linkGenes * (linkCoefficient / totalPie) + weightComponent * (weightCoefficient / totalPie);
//Debug.Log("MeasureGeneticDistance! neuronGenes: " + (neuronGenes).ToString() + " (" + genomeA.nodeNEATList.Count.ToString() + "," + genomeB.nodeNEATList.Count.ToString() +
// "), linkGenes: " + (linkGenes).ToString() + " (" + genomeA.linkNEATList.Count.ToString() + "," + genomeB.linkNEATList.Count.ToString() +
// "), weight: " + weightComponent.ToString() + ", largestWeightDelta: " + largestWeightDelta.ToString() + ", weightDeltaTotal: " + weightDeltaTotal.ToString() + "weightMatches: " + matchingGenes.ToString() +
// ", distance: " + distance.ToString());
//Debug.Log("MeasureGeneticDistance! disjoint: " + (disjointGenes).ToString() + ", excess: " + (excessGenes).ToString() + ", weight: " + (weightDeltaTotal / Mathf.Max((float)matchingGenes, 1f)).ToString() + ", distance: " + distance.ToString());
}
// else stays 0f;
return distance;
}
public Species(Species baseSpecies)
{
id = baseSpecies.id;
currentMemberCount = 0;
templateGenome = baseSpecies.templateGenome;
}
public override object Read(ES2Reader reader)
{
GenomeNEAT data = new GenomeNEAT();
Read(reader, data);
return data;
}
public Species(Species baseSpecies) {
id = baseSpecies.id;
currentMemberCount = 0;
templateGenome = baseSpecies.templateGenome;
}