public void InitShaderTexture(BrainNEAT brain)
{
if (neuronPositionsTexture == null)
{
neuronPositionsTexture = new Texture2D(brain.neuronList.Count, 1, TextureFormat.RGBAHalf, false);
}
else
{
neuronPositionsTexture.Resize(brain.neuronList.Count, 1);
}
}
public void UpdateVertexColors(BrainNEAT brain)
{
//Debug.Log("UpdateVertexColors(BrainNEAT brain) " + GetColorFromValue(brain.neuronList[0].currentValue[0]).ToString());
for (int i = 0; i < brain.neuronList.Count; i++)
{
ChangeNodeColor(i, GetColorFromNeuron(brain.neuronList[i]));
}
for (int j = 0; j < brain.connectionList.Count; j++)
{
//ChangeConnectionColor(j, GetColorFromConnection(brain.connectionList[j], brain));
}
meshBuilder.UpdateMeshColors();
}
public void UpdateNodeVertexPositions(BrainNEAT brain)
{
for (int i = 0; i < nodeVertexList.Count; i++)
{
// for all neurons:
//Debug.Log("index0: " + nodePositionsList[i].x.ToString() + ", " + nodePositionsList[i].y.ToString() + " index1: " + nodePositionsList[i].x.ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index2: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index3: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + nodePositionsList[i].y.ToString());
//float size = neuronRadius + Mathf.Abs(brain.neuronList[i].previousValue) * neuronRadius * 0.12f;
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[i].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
meshBuilder.Vertices[nodeVertexList[i][0]] = nodePositionsList[i];
meshBuilder.Vertices[nodeVertexList[i][1]] = nodePositionsList[i] + new Vector3(0f, size, 0f);
meshBuilder.Vertices[nodeVertexList[i][2]] = nodePositionsList[i] + new Vector3(size, 0f, 0f) + new Vector3(0f, size, 0f);
meshBuilder.Vertices[nodeVertexList[i][3]] = nodePositionsList[i] + new Vector3(size, 0f, 0f);
}
meshBuilder.UpdateMeshVertices();
}
private Color GetColorFromConnection(ConnectionNEAT connection, BrainNEAT brain)
{
//black = -1, white = 1
//float val01 = connection.weight[0] * 0.5f + 0.5f;
float val01 = brain.neuronList[connection.fromNodeID].currentValue[0] * connection.weight[0] * 0.2f + 0.5f;
Color newColor = new Color(val01, val01, val01);
newColor = Color.Lerp(newColor, new Color(0f, 0f, 1f), 0f);
//if (connection.nodeType == GeneNodeNEAT.GeneNodeType.In) {
// newColor = Color.Lerp(newColor, new Color(0f, 1f, 0f), 0.75f);
//}
//if (connection.nodeType == GeneNodeNEAT.GeneNodeType.Out) {
// newColor = Color.Lerp(newColor, new Color(1f, 0f, 0f), 0.75f);
//}
//Debug.Log(val01.ToString());
return(newColor);
}
//TODO: In more complete evaluators, take in an arena manager that lets you check out a room. That will return the bot/brain that was
//created for that room (request a room each time StartNewEvaluation is called, or if no rooms available at that moment, each tick until
//a room is free - then start evaluating from that moment)
public Evaluator1_FAIL(Bot bot, BrainNEAT brainPart, SensorHoming[] homingParts, Point3D homePoint, ExperimentInitArgs_Activation activation, HyperNEAT_Args hyperneatArgs = null)
{
_bot = bot;
_brainPart = brainPart;
_homingParts = homingParts;
_homePoint = homePoint;
_activation = activation;
_hyperneatArgs = hyperneatArgs;
foreach (SensorHoming homingPart in homingParts)
{
homingPart.HomePoint = homePoint;
homingPart.HomeRadius = _maxDistance * 1.25;
}
}
public void UpdateConnectionVertexPositions(BrainNEAT brain)
{
//for (int c = 0; c < brain.connectionList.Count; c++) {
//BuildLink(meshBuilder, nodePositionsList[brain.connectionList[c].fromNodeID] + offset, nodePositionsList[brain.connectionList[c].toNodeID] + offset, connectionWidth, GetColorFromValue(brain.connectionList[c].weight[0]));
//Debug.Log("BuildNew BrainMesh: from: " + nodePositionsList[brain.connectionList[c].fromNodeID].ToString() + ", to: " + nodePositionsList[brain.connectionList[c].toNodeID].ToString());
//}
for (int i = 0; i < connectionVertexList.Count; i++)
{
// for all connections:
Vector3 linkVector = new Vector3(nodePositionsList[brain.connectionList[i].toNodeID].x - nodePositionsList[brain.connectionList[i].fromNodeID].x, nodePositionsList[brain.connectionList[i].toNodeID].y - nodePositionsList[brain.connectionList[i].fromNodeID].y, nodePositionsList[brain.connectionList[i].toNodeID].z - nodePositionsList[brain.connectionList[i].fromNodeID].z);
Vector3 widthVector = new Vector3(new Vector2(linkVector.y, -linkVector.x).normalized.x, new Vector2(linkVector.y, -linkVector.x).normalized.y, 0f) * (connectionWidthMin + Mathf.Abs(brain.connectionList[i].weight[0]) * connectionWidthMin * 0.62f);
Vector3 cornerPos = new Vector3(nodePositionsList[brain.connectionList[i].fromNodeID].x - widthVector.x * 0.5f + neuronRadiusMin * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].y - widthVector.y * 0.5f + neuronRadiusMin * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].z);
//Debug.Log("index0: " + nodePositionsList[i].x.ToString() + ", " + nodePositionsList[i].y.ToString() + " index1: " + nodePositionsList[i].x.ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index2: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index3: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + nodePositionsList[i].y.ToString());
meshBuilder.Vertices[connectionVertexList[i][0]] = cornerPos;
meshBuilder.Vertices[connectionVertexList[i][1]] = cornerPos + linkVector;
meshBuilder.Vertices[connectionVertexList[i][2]] = cornerPos + linkVector + widthVector;
meshBuilder.Vertices[connectionVertexList[i][3]] = cornerPos + widthVector;
}
meshBuilder.UpdateMeshVertices();
}
public void InitShaderTexture(BrainNEAT brain) {
if (neuronPositionsTexture == null) {
neuronPositionsTexture = new Texture2D(brain.neuronList.Count, 1, TextureFormat.RGBAHalf, false);
}
else {
neuronPositionsTexture.Resize(brain.neuronList.Count, 1);
}
}
public Mesh BuildNewMesh(BrainNEAT brain) {
if(sourceCritter == null) {
Debug.Log("BuildNewMesh(BrainNEAT brain) SOURCE CRITTER NULL!!!");
}
else {
SetNeuronSegmentPositions(brain);
}
if (nodeVertexList == null) {
nodeVertexList = new List<List<int>>();
}
else {
nodeVertexList.Clear();
}
if (connectionVertexList == null) {
connectionVertexList = new List<List<int>>();
}
else {
connectionVertexList.Clear();
}
if(nodePositionsList == null) {
nodePositionsList = new List<Vector3>();
}
else {
nodePositionsList.Clear();
}
if(bezierCurveList == null) {
bezierCurveList = new List<BezierCurve>();
}
else {
bezierCurveList.Clear();
}
if(hiddenNodeIndicesList == null) {
hiddenNodeIndicesList = new List<int>(); // keep track of hidden nodes for later use
}
else {
hiddenNodeIndicesList.Clear();
}
meshBuilder = new MeshBuilder();
//Debug.Log("PRE ERROR: brain: " + brain.ToString());
//neuronRadius = 1.4f / Mathf.Max((float)brain.inputNeuronList.Count, (float)brain.outputNeuronList.Count);
//Vector3 offset = new Vector3(neuronRadius * 0.5f, neuronRadius * 0.5f, 0f);
int currentInputIndex = 0;
int currentOutputIndex = 0;
for(int i = 0; i < brain.neuronList.Count; i++) {
// go through all nodes and place them in proper spot
float xpos = 0f;
float ypos = 0f;
float zpos = 0f;
//float size = Mathf.Min((neuronRadius * brain.neuronList[i].currentValue[0] * 0.2f + 0.02f), 2.0f);
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[i].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
if (brain.neuronList[i].nodeType == GeneNodeNEAT.GeneNodeType.In) {
xpos = (float)(currentInputIndex + 1) / (float)(brain.inputNeuronList.Count + 1) - 0.5f;
ypos = 0f;
zpos = UnityEngine.Random.Range(-0.5f, 0.5f);
currentInputIndex++;
BuildNodeSphere(meshBuilder, new Vector3(xpos, ypos, zpos), size, GetColorFromNeuron(brain.neuronList[i]));
}
else if(brain.neuronList[i].nodeType == GeneNodeNEAT.GeneNodeType.Hid) {
xpos = 0.0f; // UnityEngine.Random.Range(neuronRadius, 1f - neuronRadius); //0.5f;
ypos = 0.0f; // UnityEngine.Random.Range(neuronRadius, 1f - neuronRadius); //0.5f;
zpos = UnityEngine.Random.Range(-0.5f, 0.5f);
hiddenNodeIndicesList.Add(i);
//BuildNode(meshBuilder, new Vector3(xpos, ypos, 0f), new Vector3(radius, 0f, 0f), new Vector3(0f, radius, 0f), GetColorFromValue(brain.neuronList[i].currentValue[0]));
}
else { // output
xpos = (float)(currentOutputIndex + 1) / (float)(brain.outputNeuronList.Count + 1) - 0.5f;
ypos = 1f - neuronRadiusMax;
zpos = UnityEngine.Random.Range(-0.5f, 0.5f);
currentOutputIndex++;
BuildNodeSphere(meshBuilder, new Vector3(xpos, ypos, zpos), size, GetColorFromNeuron(brain.neuronList[i]));
}
nodePositionsList.Add(new Vector3(xpos, ypos, zpos));
}
// position HiddenNodes!!
// BUILD hidden nodes:
for (int h = 0; h < hiddenNodeIndicesList.Count; h++) {
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[hiddenNodeIndicesList[h]].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
BuildNodeSphere(meshBuilder, new Vector3(nodePositionsList[hiddenNodeIndicesList[h]].x, nodePositionsList[hiddenNodeIndicesList[h]].y, nodePositionsList[hiddenNodeIndicesList[h]].z), size, GetColorFromNeuron(brain.neuronList[hiddenNodeIndicesList[h]]));
}
// CONNECTIONS!
//connectionWidth = Mathf.Max(neuronRadius * 0.1f, 0.01f);
//Debug.Log("BuildNew BrainMesh: numConnections: " + brain.connectionList.Count);
for(int c = 0; c < brain.connectionList.Count; c++) {
BezierCurve connectionBezier = new BezierCurve();
connectionBezier.points[0] = nodePositionsList[brain.connectionList[c].fromNodeID];
connectionBezier.points[1] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.333f);
connectionBezier.points[2] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.667f);
connectionBezier.points[3] = nodePositionsList[brain.connectionList[c].toNodeID];
bezierCurveList.Add(connectionBezier);
float startWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].fromNodeID].currentValue[0]) * connectionWidthMax * 0.4f), connectionWidthMax), connectionWidthMin);
float endWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].toNodeID].currentValue[0])) * connectionWidthMax * 0.4f, connectionWidthMax), connectionWidthMin);
BuildLinkBezier(meshBuilder, connectionBezier, startWidth, endWidth, GetColorFromNeuron(brain.neuronList[brain.connectionList[c].fromNodeID]), GetColorFromNeuron(brain.neuronList[brain.connectionList[c].toNodeID]));
//Debug.Log("BuildNew BrainMesh: from: " + nodePositionsList[brain.connectionList[c].fromNodeID].ToString() + ", to: " + nodePositionsList[brain.connectionList[c].toNodeID].ToString());
}
//MoveHiddenNodes(brain, 1);
return meshBuilder.CreateMesh();
}
public Mesh BuildNewMesh(BrainNEAT brain)
{
if (sourceCritter == null)
{
Debug.Log("BuildNewMesh(BrainNEAT brain) SOURCE CRITTER NULL!!!");
}
else
{
SetNeuronSegmentPositions(brain);
}
if (nodeVertexList == null)
{
nodeVertexList = new List <List <int> >();
}
else
{
nodeVertexList.Clear();
}
if (connectionVertexList == null)
{
connectionVertexList = new List <List <int> >();
}
else
{
connectionVertexList.Clear();
}
if (nodePositionsList == null)
{
nodePositionsList = new List <Vector3>();
}
else
{
nodePositionsList.Clear();
}
if (bezierCurveList == null)
{
bezierCurveList = new List <BezierCurve>();
}
else
{
bezierCurveList.Clear();
}
if (hiddenNodeIndicesList == null)
{
hiddenNodeIndicesList = new List <int>(); // keep track of hidden nodes for later use
}
else
{
hiddenNodeIndicesList.Clear();
}
meshBuilder = new MeshBuilder();
//Debug.Log("PRE ERROR: brain: " + brain.ToString());
//neuronRadius = 1.4f / Mathf.Max((float)brain.inputNeuronList.Count, (float)brain.outputNeuronList.Count);
//Vector3 offset = new Vector3(neuronRadius * 0.5f, neuronRadius * 0.5f, 0f);
int currentInputIndex = 0;
int currentOutputIndex = 0;
for (int i = 0; i < brain.neuronList.Count; i++)
{
// go through all nodes and place them in proper spot
float xpos = 0f;
float ypos = 0f;
float zpos = 0f;
//float size = Mathf.Min((neuronRadius * brain.neuronList[i].currentValue[0] * 0.2f + 0.02f), 2.0f);
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[i].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
if (brain.neuronList[i].nodeType == GeneNodeNEAT.GeneNodeType.In)
{
xpos = (float)(currentInputIndex + 1) / (float)(brain.inputNeuronList.Count + 1) - 0.5f;
ypos = 0f;
zpos = UnityEngine.Random.Range(-0.5f, 0.5f);
currentInputIndex++;
BuildNodeSphere(meshBuilder, new Vector3(xpos, ypos, zpos), size, GetColorFromNeuron(brain.neuronList[i]));
}
else if (brain.neuronList[i].nodeType == GeneNodeNEAT.GeneNodeType.Hid)
{
xpos = 0.0f; // UnityEngine.Random.Range(neuronRadius, 1f - neuronRadius); //0.5f;
ypos = 0.0f; // UnityEngine.Random.Range(neuronRadius, 1f - neuronRadius); //0.5f;
zpos = UnityEngine.Random.Range(-0.5f, 0.5f);
hiddenNodeIndicesList.Add(i);
//BuildNode(meshBuilder, new Vector3(xpos, ypos, 0f), new Vector3(radius, 0f, 0f), new Vector3(0f, radius, 0f), GetColorFromValue(brain.neuronList[i].currentValue[0]));
}
else // output
{
xpos = (float)(currentOutputIndex + 1) / (float)(brain.outputNeuronList.Count + 1) - 0.5f;
ypos = 1f - neuronRadiusMax;
zpos = UnityEngine.Random.Range(-0.5f, 0.5f);
currentOutputIndex++;
BuildNodeSphere(meshBuilder, new Vector3(xpos, ypos, zpos), size, GetColorFromNeuron(brain.neuronList[i]));
}
nodePositionsList.Add(new Vector3(xpos, ypos, zpos));
}
// position HiddenNodes!!
// BUILD hidden nodes:
for (int h = 0; h < hiddenNodeIndicesList.Count; h++)
{
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[hiddenNodeIndicesList[h]].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
BuildNodeSphere(meshBuilder, new Vector3(nodePositionsList[hiddenNodeIndicesList[h]].x, nodePositionsList[hiddenNodeIndicesList[h]].y, nodePositionsList[hiddenNodeIndicesList[h]].z), size, GetColorFromNeuron(brain.neuronList[hiddenNodeIndicesList[h]]));
}
// CONNECTIONS!
//connectionWidth = Mathf.Max(neuronRadius * 0.1f, 0.01f);
//Debug.Log("BuildNew BrainMesh: numConnections: " + brain.connectionList.Count);
for (int c = 0; c < brain.connectionList.Count; c++)
{
BezierCurve connectionBezier = new BezierCurve();
connectionBezier.points[0] = nodePositionsList[brain.connectionList[c].fromNodeID];
connectionBezier.points[1] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.333f);
connectionBezier.points[2] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.667f);
connectionBezier.points[3] = nodePositionsList[brain.connectionList[c].toNodeID];
bezierCurveList.Add(connectionBezier);
float startWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].fromNodeID].currentValue[0]) * connectionWidthMax * 0.4f), connectionWidthMax), connectionWidthMin);
float endWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].toNodeID].currentValue[0])) * connectionWidthMax * 0.4f, connectionWidthMax), connectionWidthMin);
BuildLinkBezier(meshBuilder, connectionBezier, startWidth, endWidth, GetColorFromNeuron(brain.neuronList[brain.connectionList[c].fromNodeID]), GetColorFromNeuron(brain.neuronList[brain.connectionList[c].toNodeID]));
//Debug.Log("BuildNew BrainMesh: from: " + nodePositionsList[brain.connectionList[c].fromNodeID].ToString() + ", to: " + nodePositionsList[brain.connectionList[c].toNodeID].ToString());
}
//MoveHiddenNodes(brain, 1);
return(meshBuilder.CreateMesh());
}
/// <summary>
/// Once the world is created on the worker thread, maps and bots need to be created for each room
/// NOTE: This is called from the worker thread
/// </summary>
private void Arena_WorldCreated(object sender, EventArgs e)
{
World world = Arena.WorldAccessor.World;
#region materials
MaterialManager = new MaterialManager(world);
MaterialIDs = new MaterialIDs();
// Wall
Game.Newt.v2.NewtonDynamics.Material material = new Game.Newt.v2.NewtonDynamics.Material();
material.Elasticity = ItemOptionsArco.ELASTICITY_WALL;
MaterialIDs.Wall = MaterialManager.AddMaterial(material);
// Bot
material = new Game.Newt.v2.NewtonDynamics.Material();
MaterialIDs.Bot = MaterialManager.AddMaterial(material);
// Bot Ram
material = new Game.Newt.v2.NewtonDynamics.Material();
material.Elasticity = ItemOptionsArco.ELASTICITY_BOTRAM;
MaterialIDs.BotRam = MaterialManager.AddMaterial(material);
// Exploding Bot
material = new Game.Newt.v2.NewtonDynamics.Material();
material.IsCollidable = false;
MaterialIDs.ExplodingBot = MaterialManager.AddMaterial(material);
// Weapon
material = new Game.Newt.v2.NewtonDynamics.Material();
MaterialIDs.Weapon = MaterialManager.AddMaterial(material);
// Treasure Box
material = new Game.Newt.v2.NewtonDynamics.Material();
MaterialIDs.TreasureBox = MaterialManager.AddMaterial(material);
//TODO: Uncomment these
// Collisions
//_materialManager.RegisterCollisionEvent(_materialIDs.Bot, _materialIDs.Bot, Collision_BotBot);
//_materialManager.RegisterCollisionEvent(_materialIDs.Bot, _materialIDs.Weapon, Collision_BotWeapon);
//_materialManager.RegisterCollisionEvent(_materialIDs.Weapon, _materialIDs.Weapon, Collision_WeaponWeapon);
////_materialManager.RegisterCollisionEvent(_materialIDs.Bot, _materialIDs.Wall, Collision_BotWall);
//_materialManager.RegisterCollisionEvent(_materialIDs.Weapon, _materialIDs.Wall, Collision_WeaponWall);
//_materialManager.RegisterCollisionEvent(_materialIDs.Weapon, _materialIDs.TreasureBox, Collision_WeaponTreasureBox);
//_materialManager.RegisterCollisionEvent(_materialIDs.Bot, _materialIDs.TreasureBox, Collision_BotTreasureBox);
#endregion
List <KeepItems2D> keep2Ds = new List <KeepItems2D>();
foreach (var(room, _) in Arena.AllRooms)
{
#region keep 2D
//TODO: drag plane should either be a plane or a large cylinder, based on the current (level|scene|stage|area|arena|map|place|region|zone)
// This game is 3D emulating 2D, so always have the mouse go to the XY plane
DragHitShape dragPlane = new DragHitShape();
dragPlane.SetShape_Plane(new Triangle(new Point3D(-1, -1, room.Center.Z), new Point3D(1, -1, room.Center.Z), new Point3D(0, 1, room.Center.Z)));
// This will keep objects onto that plane using forces (not velocities)
KeepItems2D keep2D = new KeepItems2D
{
SnapShape = dragPlane,
};
//keep2D.Add(room.Bot, false);
keep2Ds.Add(keep2D);
#endregion
#region bot
ShipCoreArgs core = new ShipCoreArgs()
{
World = world,
Material_Ship = MaterialIDs.Bot,
Map = room.Map,
};
//BotConstructor_Events events = new BotConstructor_Events();
//events.
// Create the bot
Bot bot = null;
if (RequestCustomBot != null)
{
bot = RequestCustomBot(core, keep2D, dragPlane, MaterialIDs);
}
else
{
BotConstruction_Result construction = BotConstructor.ConstructBot(DNA, core, ShipExtraArgs);
bot = new Bot(construction);
}
// Find some parts
BrainNEAT brainPart = bot.Parts.FirstOrDefault(o => o is BrainNEAT) as BrainNEAT;
if (brainPart == null)
{
throw new ApplicationException("Didn't find BrainNEAT part");
}
SensorHoming[] homingParts = bot.Parts.
Where(o => o is SensorHoming).
Select(o => (SensorHoming)o).
ToArray();
if (homingParts.Length == 0)
{
throw new ApplicationException("Didn't find SensorHoming part");
}
#endregion
room.Bot = bot;
room.BrainPart = brainPart;
room.HomingParts = homingParts;
foreach (SensorHoming homing in homingParts)
{
homing.HomePoint = room.Center;
homing.HomeRadius = (ROOMSIZE / 2d) * Evaluator3.MULT_HOMINGSIZE;
}
room.Map.AddItem(bot);
keep2D.Add(room.Bot, false);
}
Keep2D = keep2Ds.ToArray();
world.Updated += World_Updated;
}
public void UpdateConnectionVertexPositions(BrainNEAT brain) {
//for (int c = 0; c < brain.connectionList.Count; c++) {
//BuildLink(meshBuilder, nodePositionsList[brain.connectionList[c].fromNodeID] + offset, nodePositionsList[brain.connectionList[c].toNodeID] + offset, connectionWidth, GetColorFromValue(brain.connectionList[c].weight[0]));
//Debug.Log("BuildNew BrainMesh: from: " + nodePositionsList[brain.connectionList[c].fromNodeID].ToString() + ", to: " + nodePositionsList[brain.connectionList[c].toNodeID].ToString());
//}
for (int i = 0; i < connectionVertexList.Count; i++) {
// for all connections:
Vector3 linkVector = new Vector3(nodePositionsList[brain.connectionList[i].toNodeID].x - nodePositionsList[brain.connectionList[i].fromNodeID].x, nodePositionsList[brain.connectionList[i].toNodeID].y - nodePositionsList[brain.connectionList[i].fromNodeID].y, nodePositionsList[brain.connectionList[i].toNodeID].z - nodePositionsList[brain.connectionList[i].fromNodeID].z);
Vector3 widthVector = new Vector3(new Vector2(linkVector.y, -linkVector.x).normalized.x, new Vector2(linkVector.y, -linkVector.x).normalized.y, 0f) * (connectionWidthMin + Mathf.Abs(brain.connectionList[i].weight[0]) * connectionWidthMin * 0.62f);
Vector3 cornerPos = new Vector3(nodePositionsList[brain.connectionList[i].fromNodeID].x - widthVector.x * 0.5f + neuronRadiusMin * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].y - widthVector.y * 0.5f + neuronRadiusMin * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].z);
//Debug.Log("index0: " + nodePositionsList[i].x.ToString() + ", " + nodePositionsList[i].y.ToString() + " index1: " + nodePositionsList[i].x.ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index2: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index3: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + nodePositionsList[i].y.ToString());
meshBuilder.Vertices[connectionVertexList[i][0]] = cornerPos;
meshBuilder.Vertices[connectionVertexList[i][1]] = cornerPos + linkVector;
meshBuilder.Vertices[connectionVertexList[i][2]] = cornerPos + linkVector + widthVector;
meshBuilder.Vertices[connectionVertexList[i][3]] = cornerPos + widthVector;
}
meshBuilder.UpdateMeshVertices();
}
public void BuildBrainMesh(BrainNEAT brain) {
MiniGameManager currentGameManager = PlayerList[playingCurPlayer].masterTrialsList[playingCurTrialIndex].miniGameManager;
if (brainNetworkGO == null) {
brainNetworkGO = new GameObject("brainNetworkGO");
brainNetworkGO.AddComponent<MeshFilter>();
//Material brainNetworkMat = new Material(Shader.Find("Custom/SimpleBrainNetworkShader"));
brainNetworkGO.AddComponent<MeshRenderer>().material = brainNetworkMat;
networkVisualizer = brainNetworkGO.AddComponent<BrainNetworkVisualizer>();
if (currentGameManager.miniGameInstance.critterBeingTested != null) {
networkVisualizer.sourceCritter = currentGameManager.miniGameInstance.critterBeingTested;
}
//currentGameManager.miniGameInstance.critterBeingTested.critterSegmentMaterial.SetTexture("_NeuronPosTex", networkVisualizer.neuronPositionsTexture);
}
MiniGameCritterWalkBasic minigame = (MiniGameCritterWalkBasic)currentGameManager.miniGameInstance as MiniGameCritterWalkBasic;
networkVisualizer.InitShaderTexture(brain);
minigame.SetShaderTextures(networkVisualizer);
brainNetworkGO.GetComponent<MeshFilter>().sharedMesh = networkVisualizer.BuildNewMesh(brain);
}
public void UpdateNodeVertexPositions(BrainNEAT brain) {
for(int i = 0; i < nodeVertexList.Count; i++) {
// for all neurons:
//Debug.Log("index0: " + nodePositionsList[i].x.ToString() + ", " + nodePositionsList[i].y.ToString() + " index1: " + nodePositionsList[i].x.ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index2: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index3: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + nodePositionsList[i].y.ToString());
//float size = neuronRadius + Mathf.Abs(brain.neuronList[i].previousValue) * neuronRadius * 0.12f;
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[i].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
meshBuilder.Vertices[nodeVertexList[i][0]] = nodePositionsList[i];
meshBuilder.Vertices[nodeVertexList[i][1]] = nodePositionsList[i] + new Vector3(0f, size, 0f);
meshBuilder.Vertices[nodeVertexList[i][2]] = nodePositionsList[i] + new Vector3(size, 0f, 0f) + new Vector3(0f, size, 0f);
meshBuilder.Vertices[nodeVertexList[i][3]] = nodePositionsList[i] + new Vector3(size, 0f, 0f);
}
meshBuilder.UpdateMeshVertices();
}
private Color GetColorFromConnection(ConnectionNEAT connection, BrainNEAT brain) {
//black = -1, white = 1
//float val01 = connection.weight[0] * 0.5f + 0.5f;
float val01 = brain.neuronList[connection.fromNodeID].currentValue[0] * connection.weight[0] * 0.2f + 0.5f;
Color newColor = new Color(val01, val01, val01);
newColor = Color.Lerp(newColor, new Color(0f, 0f, 1f), 0f);
//if (connection.nodeType == GeneNodeNEAT.GeneNodeType.In) {
// newColor = Color.Lerp(newColor, new Color(0f, 1f, 0f), 0.75f);
//}
//if (connection.nodeType == GeneNodeNEAT.GeneNodeType.Out) {
// newColor = Color.Lerp(newColor, new Color(1f, 0f, 0f), 0.75f);
//}
//Debug.Log(val01.ToString());
return newColor;
}
public void MoveNeurons(BrainNEAT brain, int numIter) {
// position HiddenNodes!!
int numIterations = numIter;
List<Vector3> newNodePositionsList = new List<Vector3>();
for(int i = 0; i < nodePositionsList.Count; i++) { // Initialize new positions list
Vector3 newPositionVector = new Vector3();
newPositionVector = nodePositionsList[i];
newNodePositionsList.Add(newPositionVector);
}
//float attract = 0.007f;
//float repel = 0.0025f;
for (int phase = 0; phase < numIterations; phase++) {
// Attract NEURONS:
for (int c = 0; c < brain.connectionList.Count; c++) {
// go trhough all connections and treat them as springs
int fromNode = brain.connectionList[c].fromNodeID;
int toNode = brain.connectionList[c].toNodeID;
Vector3 linkVector = nodePositionsList[toNode] - nodePositionsList[fromNode];
if (brain.neuronList[fromNode].nodeType == GeneNodeNEAT.GeneNodeType.In) {
//linkVector += new Vector2(0f, -attract * 2.7f);
}
else if (brain.neuronList[fromNode].nodeType == GeneNodeNEAT.GeneNodeType.Out) {
//linkVector += new Vector2(0f, attract * 2.7f);
}
float dist = Mathf.Max(linkVector.sqrMagnitude, 0.02f);
newNodePositionsList[fromNode] += linkVector * attractByConnections * dist; // move fromNode towards toNode proportionally based on its distance
newNodePositionsList[toNode] -= linkVector * attractByConnections * dist; // move fromNode towards toNode proportionally based on its distance
}
// REPEL NEURONS:
for (int j = 0; j < nodePositionsList.Count; j++) { // for all nodes
for (int k = 0; k < nodePositionsList.Count; k++) { // go through all nodes
if (j != k) { // if not comparing to itself
Vector3 vectorToNode = (nodePositionsList[k] - nodePositionsList[j]);
float dist = Mathf.Max(vectorToNode.magnitude, 0.01f);
// repel from each node:
if (dist < neuronRepelMaxDistance) {
newNodePositionsList[j] -= vectorToNode * neuronRepelForce / dist;
newNodePositionsList[k] += vectorToNode * neuronRepelForce / dist;
}
}
}
// For each node, if not hidden, move towards its worldPos:
if (brain.neuronList[j].nodeType != GeneNodeNEAT.GeneNodeType.Hid) {
Vector3 vectorToSegmentPos = (brain.neuronList[j].worldPos - nodePositionsList[j]);
float dist = Mathf.Max(vectorToSegmentPos.sqrMagnitude, 0.01f);
newNodePositionsList[j] += vectorToSegmentPos * attractToCritterPos;
//Debug.Log("brain.neuronList[" + j.ToString() + "] worldPos: " + brain.neuronList[j].worldPos.ToString() + ", nodePos: " + nodePositionsList[j].ToString());
}
// build texture to pass to shader:
Vector3 position = nodePositionsList[j];
neuronPositionsTexture.SetPixel(j, 1, new Color(position.x, position.y, position.z, brain.neuronList[j].currentValue[0]));
}
// Apply new Neuron positions to master list:
for (int p = 0; p < nodePositionsList.Count; p++) { // Initialize new positions list
//Vector3 newPositionVector = new Vector3();
nodePositionsList[p] = newNodePositionsList[p];
}
// BEZIER CURVES:
for (int c = 0; c < brain.connectionList.Count; c++) {
bezierCurveList[c].points[0] = nodePositionsList[brain.connectionList[c].fromNodeID];
//bezierCurveList[c].points[1] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.333f);
//bezierCurveList[c].points[2] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.667f);
bezierCurveList[c].points[3] = nodePositionsList[brain.connectionList[c].toNodeID];
for (int b = 0; b < bezierCurveList.Count; b++) {
// Go through all other bezierCurves and repel from others
if (b != c) { // if not comparing to itself:
for (int control = 0; control < 4; control++) { // go through each of the 4 points in the other bezierCurve connection:
Vector3 vectorToControlPoint1 = bezierCurveList[b].points[control] - bezierCurveList[c].points[1];
float distance = Mathf.Max(vectorToControlPoint1.sqrMagnitude, 0.02f);
// The middle control points in the current Beziercurve are repelled from ALL OTHER bezier curve control points!
if (distance < neuronRepelMaxDistance) {
bezierCurveList[c].points[1] -= vectorToControlPoint1 * bezierRepelForce * distance;
bezierCurveList[c].points[2] -= vectorToControlPoint1 * bezierRepelForce * distance;
}
}
}
}
// ATTRACT to rest position!
Vector3 vectorControl1ToRest = Vector3.Lerp(bezierCurveList[c].points[0], bezierCurveList[c].points[3], 0.333f) - bezierCurveList[c].points[1];
float dist1 = Mathf.Max(vectorControl1ToRest.sqrMagnitude, 0.02f);
Vector3 vectorControl2ToRest = Vector3.Lerp(bezierCurveList[c].points[0], bezierCurveList[c].points[3], 0.667f) - bezierCurveList[c].points[2];
float dist2 = Mathf.Max(vectorControl2ToRest.sqrMagnitude, 0.02f);
bezierCurveList[c].points[1] += vectorControl1ToRest * attractToControlPoints * dist1;
bezierCurveList[c].points[2] += vectorControl2ToRest * attractToControlPoints * dist2;
}
neuronPositionsTexture.Apply();
}
//meshBuilder.UpdateMeshVertices();
}
public void MoveNeurons(BrainNEAT brain, int numIter)
{
// position HiddenNodes!!
int numIterations = numIter;
List <Vector3> newNodePositionsList = new List <Vector3>();
for (int i = 0; i < nodePositionsList.Count; i++) // Initialize new positions list
{
Vector3 newPositionVector = new Vector3();
newPositionVector = nodePositionsList[i];
newNodePositionsList.Add(newPositionVector);
}
//float attract = 0.007f;
//float repel = 0.0025f;
for (int phase = 0; phase < numIterations; phase++)
{
// Attract NEURONS:
for (int c = 0; c < brain.connectionList.Count; c++)
{
// go trhough all connections and treat them as springs
int fromNode = brain.connectionList[c].fromNodeID;
int toNode = brain.connectionList[c].toNodeID;
Vector3 linkVector = nodePositionsList[toNode] - nodePositionsList[fromNode];
if (brain.neuronList[fromNode].nodeType == GeneNodeNEAT.GeneNodeType.In)
{
//linkVector += new Vector2(0f, -attract * 2.7f);
}
else if (brain.neuronList[fromNode].nodeType == GeneNodeNEAT.GeneNodeType.Out)
{
//linkVector += new Vector2(0f, attract * 2.7f);
}
float dist = Mathf.Max(linkVector.sqrMagnitude, 0.02f);
newNodePositionsList[fromNode] += linkVector * attractByConnections * dist; // move fromNode towards toNode proportionally based on its distance
newNodePositionsList[toNode] -= linkVector * attractByConnections * dist; // move fromNode towards toNode proportionally based on its distance
}
// REPEL NEURONS:
for (int j = 0; j < nodePositionsList.Count; j++) // for all nodes
{
for (int k = 0; k < nodePositionsList.Count; k++) // go through all nodes
{
if (j != k) // if not comparing to itself
{
Vector3 vectorToNode = (nodePositionsList[k] - nodePositionsList[j]);
float dist = Mathf.Max(vectorToNode.magnitude, 0.01f);
// repel from each node:
if (dist < neuronRepelMaxDistance)
{
newNodePositionsList[j] -= vectorToNode * neuronRepelForce / dist;
newNodePositionsList[k] += vectorToNode * neuronRepelForce / dist;
}
}
}
// For each node, if not hidden, move towards its worldPos:
if (brain.neuronList[j].nodeType != GeneNodeNEAT.GeneNodeType.Hid)
{
Vector3 vectorToSegmentPos = (brain.neuronList[j].worldPos - nodePositionsList[j]);
float dist = Mathf.Max(vectorToSegmentPos.sqrMagnitude, 0.01f);
newNodePositionsList[j] += vectorToSegmentPos * attractToCritterPos;
//Debug.Log("brain.neuronList[" + j.ToString() + "] worldPos: " + brain.neuronList[j].worldPos.ToString() + ", nodePos: " + nodePositionsList[j].ToString());
}
// build texture to pass to shader:
Vector3 position = nodePositionsList[j];
neuronPositionsTexture.SetPixel(j, 1, new Color(position.x, position.y, position.z, brain.neuronList[j].currentValue[0]));
}
// Apply new Neuron positions to master list:
for (int p = 0; p < nodePositionsList.Count; p++) // Initialize new positions list
//Vector3 newPositionVector = new Vector3();
{
nodePositionsList[p] = newNodePositionsList[p];
}
// BEZIER CURVES:
for (int c = 0; c < brain.connectionList.Count; c++)
{
bezierCurveList[c].points[0] = nodePositionsList[brain.connectionList[c].fromNodeID];
//bezierCurveList[c].points[1] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.333f);
//bezierCurveList[c].points[2] = Vector3.Lerp(nodePositionsList[brain.connectionList[c].fromNodeID], nodePositionsList[brain.connectionList[c].toNodeID], 0.667f);
bezierCurveList[c].points[3] = nodePositionsList[brain.connectionList[c].toNodeID];
for (int b = 0; b < bezierCurveList.Count; b++)
{
// Go through all other bezierCurves and repel from others
if (b != c) // if not comparing to itself:
{
for (int control = 0; control < 4; control++) // go through each of the 4 points in the other bezierCurve connection:
{
Vector3 vectorToControlPoint1 = bezierCurveList[b].points[control] - bezierCurveList[c].points[1];
float distance = Mathf.Max(vectorToControlPoint1.sqrMagnitude, 0.02f);
// The middle control points in the current Beziercurve are repelled from ALL OTHER bezier curve control points!
if (distance < neuronRepelMaxDistance)
{
bezierCurveList[c].points[1] -= vectorToControlPoint1 * bezierRepelForce * distance;
bezierCurveList[c].points[2] -= vectorToControlPoint1 * bezierRepelForce * distance;
}
}
}
}
// ATTRACT to rest position!
Vector3 vectorControl1ToRest = Vector3.Lerp(bezierCurveList[c].points[0], bezierCurveList[c].points[3], 0.333f) - bezierCurveList[c].points[1];
float dist1 = Mathf.Max(vectorControl1ToRest.sqrMagnitude, 0.02f);
Vector3 vectorControl2ToRest = Vector3.Lerp(bezierCurveList[c].points[0], bezierCurveList[c].points[3], 0.667f) - bezierCurveList[c].points[2];
float dist2 = Mathf.Max(vectorControl2ToRest.sqrMagnitude, 0.02f);
bezierCurveList[c].points[1] += vectorControl1ToRest * attractToControlPoints * dist1;
bezierCurveList[c].points[2] += vectorControl2ToRest * attractToControlPoints * dist2;
}
neuronPositionsTexture.Apply();
}
//meshBuilder.UpdateMeshVertices();
}
public void SetNeuronSegmentPositions(BrainNEAT brain)
{
int currentInputIndex = 0;
int currentOutputIndex = 0;
// Check for ANGLE SENSORS:
for (int i = 0; i < sourceCritter.segaddonJointAngleSensorList.Count; i++)
{
if (sourceCritter.critterSegmentList[sourceCritter.segaddonJointAngleSensorList[i].segmentID].GetComponent <CritterSegment>().sourceNode.jointLink.jointType == CritterJointLink.JointType.DualXY)
{
// Add an extra one if it's a dual Joint
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointAngleSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointAngleSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonContactSensorList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonContactSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonRaycastSensorList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonRaycastSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonCompassSensor1DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonCompassSensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonCompassSensor3DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonCompassSensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonPositionSensor1DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonPositionSensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonPositionSensor3DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonPositionSensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonRotationSensor1DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonRotationSensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonRotationSensor3DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonRotationSensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonVelocitySensor1DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonVelocitySensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonVelocitySensor3DList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonVelocitySensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonAltimeterList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonAltimeterList[i].segmentID].transform.position;
currentInputIndex++;
}
// Outputs:
for (int i = 0; i < sourceCritter.segaddonJointMotorList.Count; i++)
{
if (sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].GetComponent <CritterSegment>().sourceNode.jointLink.jointType == CritterJointLink.JointType.DualXY)
{
// Add an extra one if it's a dual Joint
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.position - sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.forward * sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.localScale.z * 0.5f;
currentOutputIndex++;
}
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.position - sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.forward * sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.localScale.z * 0.5f;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonThrusterEffector1DList.Count; i++)
{
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonThrusterEffector1DList[i].segmentID].transform.position;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonThrusterEffector3DList.Count; i++)
{
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonThrusterEffector3DList[i].segmentID].transform.position;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonTorqueEffector1DList.Count; i++)
{
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonTorqueEffector1DList[i].segmentID].transform.position;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonTorqueEffector3DList.Count; i++)
{
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonTorqueEffector3DList[i].segmentID].transform.position;
currentOutputIndex++;
}
// More Inputs:
for (int i = 0; i < sourceCritter.segaddonOscillatorInputList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonOscillatorInputList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonValueInputList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonValueInputList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonTimerInputList.Count; i++)
{
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonTimerInputList[i].segmentID].transform.position;
currentInputIndex++;
}
}
public void UpdateVertexColors(BrainNEAT brain) {
//Debug.Log("UpdateVertexColors(BrainNEAT brain) " + GetColorFromValue(brain.neuronList[0].currentValue[0]).ToString());
for (int i = 0; i < brain.neuronList.Count; i++) {
ChangeNodeColor(i, GetColorFromNeuron(brain.neuronList[i]));
}
for (int j = 0; j < brain.connectionList.Count; j++) {
//ChangeConnectionColor(j, GetColorFromConnection(brain.connectionList[j], brain));
}
meshBuilder.UpdateMeshColors();
}
public void UpdateNodeVertexPositionsSphere(BrainNEAT brain)
{
for (int n = 0; n < nodeVertexList.Count; n++)
{
// for all neurons:
//float size = Mathf.Min((neuronRadius * brain.neuronList[n].currentValue[0] * 0.2f + 0.02f), 2.0f);
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[n].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
int currentVertexIndex = 0;
if (nodePositionsList == null)
{
//Debug.Log("if(nodePositionsList == null) {");
}
else
{
//Debug.Log("if(nodePositionsList != null) {" + nodePositionsList.Count.ToString() + ", n: " + n.ToString() + ", fromNode: " + brain.connectionList[n].fromNodeID.ToString());
}
Vector3 offset = nodePositionsList[n] - new Vector3(0f, size, 0f);
int m_HeightSegmentCount = 4;
int m_RadialSegmentCount = 4;
float m_VerticalScale = 1f;
Quaternion rotation = Quaternion.identity;
//the angle increment per height segment:
float angleInc = Mathf.PI / m_HeightSegmentCount;
//the vertical (scaled) radius of the sphere:
float verticalRadius = size * m_VerticalScale;
//build the rings:
for (int i = 0; i <= m_HeightSegmentCount; i++)
{
Vector3 centrePos = Vector3.zero;
//calculate a height offset and radius based on a vertical circle calculation:
centrePos.y = -Mathf.Cos(angleInc * i);
float radius = Mathf.Sin(angleInc * i);
//calculate the slope of the shpere at this ring based on the height and radius:
Vector2 slope = new Vector3(-centrePos.y / m_VerticalScale, radius);
slope.Normalize();
//multiply the unit height by the vertical radius, and then add the radius to the height to make this sphere originate from its base rather than its centre:
centrePos.y = centrePos.y * verticalRadius + verticalRadius;
//scale the radius by the one stored in the partData:
radius *= size;
//calculate the final position of the ring centre:
Vector3 finalRingCentre = rotation * centrePos + offset;
//V coordinate:
float v = (float)i / m_HeightSegmentCount;
//build the ring:
//BuildRing(meshBuilder, m_RadialSegmentCount, finalRingCentre, radius, v, i > 0, rotation, slope);
float angleIncrement = (Mathf.PI * 2.0f) / m_RadialSegmentCount;
for (int j = 0; j <= m_RadialSegmentCount; j++)
{
float angle = angleIncrement * j;
Vector3 unitPosition = Vector3.zero;
unitPosition.x = Mathf.Cos(angle);
unitPosition.z = Mathf.Sin(angle);
float normalVertical = -slope.x;
float normalHorizontal = slope.y;
Vector3 normal = unitPosition * normalHorizontal;
normal.y = normalVertical;
normal = rotation * normal;
unitPosition = rotation * unitPosition;
meshBuilder.Vertices[nodeVertexList[n][currentVertexIndex]] = finalRingCentre + unitPosition * radius;
currentVertexIndex++;
}
}
}
meshBuilder.UpdateMeshVertices();
}
public void SetNeuronSegmentPositions(BrainNEAT brain) {
int currentInputIndex = 0;
int currentOutputIndex = 0;
// Check for ANGLE SENSORS:
for(int i = 0; i < sourceCritter.segaddonJointAngleSensorList.Count; i++) {
if (sourceCritter.critterSegmentList[sourceCritter.segaddonJointAngleSensorList[i].segmentID].GetComponent<CritterSegment>().sourceNode.jointLink.jointType == CritterJointLink.JointType.DualXY) {
// Add an extra one if it's a dual Joint
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointAngleSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointAngleSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
for(int i = 0; i < sourceCritter.segaddonContactSensorList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonContactSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonRaycastSensorList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonRaycastSensorList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonCompassSensor1DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonCompassSensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonCompassSensor3DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonCompassSensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonPositionSensor1DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonPositionSensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonPositionSensor3DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonPositionSensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonRotationSensor1DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonRotationSensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonRotationSensor3DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonRotationSensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonVelocitySensor1DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonVelocitySensor1DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonVelocitySensor3DList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonVelocitySensor3DList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonAltimeterList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonAltimeterList[i].segmentID].transform.position;
currentInputIndex++;
}
// Outputs:
for (int i = 0; i < sourceCritter.segaddonJointMotorList.Count; i++) {
if (sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].GetComponent<CritterSegment>().sourceNode.jointLink.jointType == CritterJointLink.JointType.DualXY) {
// Add an extra one if it's a dual Joint
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.position - sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.forward * sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.localScale.z * 0.5f;
currentOutputIndex++;
}
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.position - sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.forward * sourceCritter.critterSegmentList[sourceCritter.segaddonJointMotorList[i].segmentID].transform.localScale.z * 0.5f;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonThrusterEffector1DList.Count; i++) {
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonThrusterEffector1DList[i].segmentID].transform.position;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonThrusterEffector3DList.Count; i++) {
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonThrusterEffector3DList[i].segmentID].transform.position;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonTorqueEffector1DList.Count; i++) {
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonTorqueEffector1DList[i].segmentID].transform.position;
currentOutputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonTorqueEffector3DList.Count; i++) {
brain.outputNeuronList[currentOutputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonTorqueEffector3DList[i].segmentID].transform.position;
currentOutputIndex++;
}
// More Inputs:
for (int i = 0; i < sourceCritter.segaddonOscillatorInputList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonOscillatorInputList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonValueInputList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonValueInputList[i].segmentID].transform.position;
currentInputIndex++;
}
for (int i = 0; i < sourceCritter.segaddonTimerInputList.Count; i++) {
brain.inputNeuronList[currentInputIndex].worldPos = sourceCritter.critterSegmentList[sourceCritter.segaddonTimerInputList[i].segmentID].transform.position;
currentInputIndex++;
}
}
public void UpdateConnectionVertexPositionsBezier(BrainNEAT brain)
{
for (int c = 0; c < connectionVertexList.Count; c++)
{
// for all connections:
/*Vector3 linkVector = new Vector3(nodePositionsList[brain.connectionList[i].toNodeID].x - nodePositionsList[brain.connectionList[i].fromNodeID].x, nodePositionsList[brain.connectionList[i].toNodeID].y - nodePositionsList[brain.connectionList[i].fromNodeID].y, nodePositionsList[brain.connectionList[i].toNodeID].z - nodePositionsList[brain.connectionList[i].fromNodeID].z);
* Vector3 widthVector = new Vector3(new Vector2(linkVector.y, -linkVector.x).normalized.x, new Vector2(linkVector.y, -linkVector.x).normalized.y, 0f) * (connectionWidth + Mathf.Abs(brain.connectionList[i].weight[0]) * connectionWidth * 0.62f);
* Vector3 cornerPos = new Vector3(nodePositionsList[brain.connectionList[i].fromNodeID].x - widthVector.x * 0.5f + neuronRadius * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].y - widthVector.y * 0.5f + neuronRadius * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].z);
* //Debug.Log("index0: " + nodePositionsList[i].x.ToString() + ", " + nodePositionsList[i].y.ToString() + " index1: " + nodePositionsList[i].x.ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index2: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index3: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + nodePositionsList[i].y.ToString());
* meshBuilder.Vertices[connectionVertexList[i][0]] = cornerPos;
* meshBuilder.Vertices[connectionVertexList[i][1]] = cornerPos + linkVector;
* meshBuilder.Vertices[connectionVertexList[i][2]] = cornerPos + linkVector + widthVector;
* meshBuilder.Vertices[connectionVertexList[i][3]] = cornerPos + widthVector;
*/
int currentVertexIndex = 0;
//float width = connectionWidth; // brain.neuronList[brain.connectionList[c].fromNodeID].currentValue[0];
Color colorStart = GetColorFromNeuron(brain.neuronList[brain.connectionList[c].fromNodeID]);
Color colorEnd = GetColorFromNeuron(brain.neuronList[brain.connectionList[c].toNodeID]);
float startWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].fromNodeID].currentValue[0])) * neuronRadiusMaxValue, connectionWidthMax), connectionWidthMin);
float endWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].toNodeID].currentValue[0])) * neuronRadiusMaxValue, connectionWidthMax), connectionWidthMin);
float m_splineStartRadius = startWidth;
float m_splineEndRadius = endWidth;
int m_splineHeightSegmentCount = 8;
int m_splineRadialSegmentCount = 4;
float tInc = 1f / m_splineHeightSegmentCount; // How many subdivisions along the length of the spline
for (int i = 0; i <= m_splineHeightSegmentCount; i++)
{
float t = tInc * (float)i;
Vector3 ringCenter = bezierCurveList[c].GetPoint(t);
Vector3 dir = bezierCurveList[c].GetDirection(t);
Quaternion rot = Quaternion.identity;
if (dir != Vector3.zero)
{
rot.SetLookRotation(dir);
}
float radius = ((1f - t) * m_splineStartRadius) + (t * m_splineEndRadius);
// Construct the mesh Ring!
//BuildBezierCurveRing(meshBuilder, m_splineRadialSegmentCount, ringCenter, radius, t, i > 0, rot);
//protected void BuildBezierCurveRing(MeshBuilder meshBuilder, int segmentCount, Vector3 center, float radius, float v, bool buildTriangles, Quaternion rotation) {
float angleInc = (Mathf.PI * 2.0f) / m_splineRadialSegmentCount;
for (int j = 0; j <= m_splineRadialSegmentCount; j++)
{
float angle = angleInc * j;
Vector3 unitPosition = Vector3.zero;
unitPosition.x = Mathf.Cos(angle);
unitPosition.y = Mathf.Sin(angle);
unitPosition = rot * unitPosition;
Vector3 normal = unitPosition;
//meshBuilder.Vertices[] = ringCenter + unitPosition * radius;
meshBuilder.Vertices[connectionVertexList[c][currentVertexIndex]] = ringCenter + unitPosition * radius;
meshBuilder.Colors[connectionVertexList[c][currentVertexIndex]] = Color.Lerp(colorStart, colorEnd, t);
currentVertexIndex++;
//meshBuilder.Vertices.Add(ringCenter + unitPosition * radius);
//meshBuilder.Normals.Add(normal);
//meshBuilder.UVs.Add(new Vector2((float)i / segmentCount, v));
//meshBuilder.UVs.Add(new Vector2((float)j / m_splineRadialSegmentCount, t));
//verticesList.Add(meshBuilder.Vertices.Count - 1);
//meshBuilder.Colors.Add(color);
/*if (j > 0 && i > 0) {
* //Debug.Log ("buildTriangles!");
* int baseIndex = meshBuilder.Vertices.Count - 1;
*
* int vertsPerRow = m_splineRadialSegmentCount + 1;
*
* int index0 = baseIndex;
* int index1 = baseIndex - 1;
* int index2 = baseIndex - vertsPerRow;
* int index3 = baseIndex - vertsPerRow - 1;
*
* meshBuilder.AddTriangle(index1, index2, index0);
* meshBuilder.AddTriangle(index1, index3, index2);
* }*/
}
}
}
meshBuilder.UpdateMeshVertices();
}
public void UpdateNodeVertexPositionsSphere(BrainNEAT brain) {
for (int n = 0; n < nodeVertexList.Count; n++) {
// for all neurons:
//float size = Mathf.Min((neuronRadius * brain.neuronList[n].currentValue[0] * 0.2f + 0.02f), 2.0f);
float size = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[n].currentValue[0])) * neuronRadiusMaxValue, neuronRadiusMax), neuronRadiusMin);
int currentVertexIndex = 0;
if(nodePositionsList == null) {
//Debug.Log("if(nodePositionsList == null) {");
}
else {
//Debug.Log("if(nodePositionsList != null) {" + nodePositionsList.Count.ToString() + ", n: " + n.ToString() + ", fromNode: " + brain.connectionList[n].fromNodeID.ToString());
}
Vector3 offset = nodePositionsList[n] - new Vector3(0f, size, 0f);
int m_HeightSegmentCount = 4;
int m_RadialSegmentCount = 4;
float m_VerticalScale = 1f;
Quaternion rotation = Quaternion.identity;
//the angle increment per height segment:
float angleInc = Mathf.PI / m_HeightSegmentCount;
//the vertical (scaled) radius of the sphere:
float verticalRadius = size * m_VerticalScale;
//build the rings:
for (int i = 0; i <= m_HeightSegmentCount; i++) {
Vector3 centrePos = Vector3.zero;
//calculate a height offset and radius based on a vertical circle calculation:
centrePos.y = -Mathf.Cos(angleInc * i);
float radius = Mathf.Sin(angleInc * i);
//calculate the slope of the shpere at this ring based on the height and radius:
Vector2 slope = new Vector3(-centrePos.y / m_VerticalScale, radius);
slope.Normalize();
//multiply the unit height by the vertical radius, and then add the radius to the height to make this sphere originate from its base rather than its centre:
centrePos.y = centrePos.y * verticalRadius + verticalRadius;
//scale the radius by the one stored in the partData:
radius *= size;
//calculate the final position of the ring centre:
Vector3 finalRingCentre = rotation * centrePos + offset;
//V coordinate:
float v = (float)i / m_HeightSegmentCount;
//build the ring:
//BuildRing(meshBuilder, m_RadialSegmentCount, finalRingCentre, radius, v, i > 0, rotation, slope);
float angleIncrement = (Mathf.PI * 2.0f) / m_RadialSegmentCount;
for (int j = 0; j <= m_RadialSegmentCount; j++) {
float angle = angleIncrement * j;
Vector3 unitPosition = Vector3.zero;
unitPosition.x = Mathf.Cos(angle);
unitPosition.z = Mathf.Sin(angle);
float normalVertical = -slope.x;
float normalHorizontal = slope.y;
Vector3 normal = unitPosition * normalHorizontal;
normal.y = normalVertical;
normal = rotation * normal;
unitPosition = rotation * unitPosition;
meshBuilder.Vertices[nodeVertexList[n][currentVertexIndex]] = finalRingCentre + unitPosition * radius;
currentVertexIndex++;
}
}
}
meshBuilder.UpdateMeshVertices();
}
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 void UpdateConnectionVertexPositionsBezier(BrainNEAT brain) {
for (int c = 0; c < connectionVertexList.Count; c++) {
// for all connections:
/*Vector3 linkVector = new Vector3(nodePositionsList[brain.connectionList[i].toNodeID].x - nodePositionsList[brain.connectionList[i].fromNodeID].x, nodePositionsList[brain.connectionList[i].toNodeID].y - nodePositionsList[brain.connectionList[i].fromNodeID].y, nodePositionsList[brain.connectionList[i].toNodeID].z - nodePositionsList[brain.connectionList[i].fromNodeID].z);
Vector3 widthVector = new Vector3(new Vector2(linkVector.y, -linkVector.x).normalized.x, new Vector2(linkVector.y, -linkVector.x).normalized.y, 0f) * (connectionWidth + Mathf.Abs(brain.connectionList[i].weight[0]) * connectionWidth * 0.62f);
Vector3 cornerPos = new Vector3(nodePositionsList[brain.connectionList[i].fromNodeID].x - widthVector.x * 0.5f + neuronRadius * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].y - widthVector.y * 0.5f + neuronRadius * 0.5f, nodePositionsList[brain.connectionList[i].fromNodeID].z);
//Debug.Log("index0: " + nodePositionsList[i].x.ToString() + ", " + nodePositionsList[i].y.ToString() + " index1: " + nodePositionsList[i].x.ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index2: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + (nodePositionsList[i].y + neuronRadius).ToString() + " index3: " + (nodePositionsList[i].x + neuronRadius).ToString() + ", " + nodePositionsList[i].y.ToString());
meshBuilder.Vertices[connectionVertexList[i][0]] = cornerPos;
meshBuilder.Vertices[connectionVertexList[i][1]] = cornerPos + linkVector;
meshBuilder.Vertices[connectionVertexList[i][2]] = cornerPos + linkVector + widthVector;
meshBuilder.Vertices[connectionVertexList[i][3]] = cornerPos + widthVector;
*/
int currentVertexIndex = 0;
//float width = connectionWidth; // brain.neuronList[brain.connectionList[c].fromNodeID].currentValue[0];
Color colorStart = GetColorFromNeuron(brain.neuronList[brain.connectionList[c].fromNodeID]);
Color colorEnd = GetColorFromNeuron(brain.neuronList[brain.connectionList[c].toNodeID]);
float startWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].fromNodeID].currentValue[0])) * neuronRadiusMaxValue, connectionWidthMax), connectionWidthMin);
float endWidth = Mathf.Max(Mathf.Min((Mathf.Abs(brain.neuronList[brain.connectionList[c].toNodeID].currentValue[0])) * neuronRadiusMaxValue, connectionWidthMax), connectionWidthMin);
float m_splineStartRadius = startWidth;
float m_splineEndRadius = endWidth;
int m_splineHeightSegmentCount = 8;
int m_splineRadialSegmentCount = 4;
float tInc = 1f / m_splineHeightSegmentCount; // How many subdivisions along the length of the spline
for (int i = 0; i <= m_splineHeightSegmentCount; i++) {
float t = tInc * (float)i;
Vector3 ringCenter = bezierCurveList[c].GetPoint(t);
Vector3 dir = bezierCurveList[c].GetDirection(t);
Quaternion rot = Quaternion.identity;
if(dir != Vector3.zero) {
rot.SetLookRotation(dir);
}
float radius = ((1f - t) * m_splineStartRadius) + (t * m_splineEndRadius);
// Construct the mesh Ring!
//BuildBezierCurveRing(meshBuilder, m_splineRadialSegmentCount, ringCenter, radius, t, i > 0, rot);
//protected void BuildBezierCurveRing(MeshBuilder meshBuilder, int segmentCount, Vector3 center, float radius, float v, bool buildTriangles, Quaternion rotation) {
float angleInc = (Mathf.PI * 2.0f) / m_splineRadialSegmentCount;
for (int j = 0; j <= m_splineRadialSegmentCount; j++) {
float angle = angleInc * j;
Vector3 unitPosition = Vector3.zero;
unitPosition.x = Mathf.Cos(angle);
unitPosition.y = Mathf.Sin(angle);
unitPosition = rot * unitPosition;
Vector3 normal = unitPosition;
//meshBuilder.Vertices[] = ringCenter + unitPosition * radius;
meshBuilder.Vertices[connectionVertexList[c][currentVertexIndex]] = ringCenter + unitPosition * radius;
meshBuilder.Colors[connectionVertexList[c][currentVertexIndex]] = Color.Lerp(colorStart, colorEnd, t);
currentVertexIndex++;
//meshBuilder.Vertices.Add(ringCenter + unitPosition * radius);
//meshBuilder.Normals.Add(normal);
//meshBuilder.UVs.Add(new Vector2((float)i / segmentCount, v));
//meshBuilder.UVs.Add(new Vector2((float)j / m_splineRadialSegmentCount, t));
//verticesList.Add(meshBuilder.Vertices.Count - 1);
//meshBuilder.Colors.Add(color);
/*if (j > 0 && i > 0) {
//Debug.Log ("buildTriangles!");
int baseIndex = meshBuilder.Vertices.Count - 1;
int vertsPerRow = m_splineRadialSegmentCount + 1;
int index0 = baseIndex;
int index1 = baseIndex - 1;
int index2 = baseIndex - vertsPerRow;
int index3 = baseIndex - vertsPerRow - 1;
meshBuilder.AddTriangle(index1, index2, index0);
meshBuilder.AddTriangle(index1, index3, index2);
}*/
}
}
}
meshBuilder.UpdateMeshVertices();
}
private void BrainNEAT_Click(object sender, RoutedEventArgs e)
{
try
{
if (_experiment == null || _ea == null)
{
//NOTE: Just doing this for laziness. I don't want to write a bunch of logic to train a phenome up front
MessageBox.Show("Need to have a running experiment", this.Title, MessageBoxButton.OK, MessageBoxImage.Warning);
return;
}
// Get a genome
NeatGenome genome = _ea.CurrentChampGenome;
// Create a phenome
IBlackBox phenome = ExperimentNEATBase.GetBlackBox(genome, _experimentArgs.Activation, _hyperneatArgs);
// Instantiate a BrainNEAT
EditorOptions options = new EditorOptions();
ItemOptions itemOptions = new ItemOptions();
Container energy = new Container()
{
QuantityMax = 1000,
QuantityCurrent = 1000,
};
BrainNEATDNA dnaBrain = new BrainNEATDNA()
{
PartType = BrainNEAT.PARTTYPE, Position = new Point3D(0, 0, 0), Orientation = Quaternion.Identity, Scale = new Vector3D(1, 1, 1)
};
BrainNEAT brain = new BrainNEAT(options, itemOptions, dnaBrain, energy);
brain.SetPhenome(phenome, genome, _experimentArgs.Activation, _hyperneatArgs);
for (int cntr = 0; cntr < 100; cntr++)
{
foreach (INeuron neuron in brain.Neruons_Writeonly)
{
neuron.SetValue(StaticRandom.NextDouble(-2.5, 2.5));
}
brain.Update_AnyThread(1);
}
#region save/load test2
// let BrainNEAT do the save/load
BrainNEATDNA dna2 = (BrainNEATDNA)brain.GetNewDNA();
string dna2Text = XamlServices.Save(dna2).Replace('"', '\'');
BrainNEAT brain2 = new BrainNEAT(options, itemOptions, dna2, energy);
for (int cntr = 0; cntr < 100; cntr++)
{
foreach (INeuron neuron in brain2.Neruons_Writeonly)
{
neuron.SetValue(StaticRandom.NextDouble(-2.5, 2.5));
}
brain2.Update_AnyThread(1);
}
BrainNEATDNA dna3 = (BrainNEATDNA)brain2.GetNewDNA();
BrainNEAT brain3 = new BrainNEAT(options, itemOptions, dna3, energy);
for (int cntr = 0; cntr < 100; cntr++)
{
foreach (INeuron neuron in brain3.Neruons_Writeonly)
{
neuron.SetValue(StaticRandom.NextDouble(-2.5, 2.5));
}
brain3.Update_AnyThread(1);
}
#endregion
#region save/load test1
// initial test, building minimum necessary dna
BrainNEATDNA brainDNA = new BrainNEATDNA()
{
Activation = _experimentArgs.Activation,
Hyper = _hyperneatArgs,
NEATPositions_Input = brain.Neruons_Readonly.Select(o => o.Position).ToArray(),
NEATPositions_Output = brain.Neruons_Writeonly.Select(o => o.Position).ToArray(),
Genome = ExperimentNEATBase.SavePopulation(new[] { genome }),
};
// Make sure this can be serialized/deserialized
string testString = XamlServices.Save(brainDNA);
brainDNA = UtilityCore.Clone(brainDNA);
List <NeatGenome> genomeList = null;
if (_hyperneatArgs == null)
{
genomeList = ExperimentNEATBase.LoadPopulation(brainDNA.Genome, brainDNA.Activation, brainDNA.NEATPositions_Input.Length, brainDNA.NEATPositions_Output.Length);
}
else
{
genomeList = ExperimentNEATBase.LoadPopulation(brainDNA.Genome, brainDNA.Activation, _hyperneatArgs);
}
#endregion
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString(), this.Title, MessageBoxButton.OK, MessageBoxImage.Error);
}
}
