public WormList(float fitness, NeuronalNetwork controller, int foodeaten, Color color)
{
Controller = new NeuronalNetwork(controller);
Fitness = fitness;
FoodEaten = foodeaten;
WormColor = color;
}
public void Deserialize(BinaryReader reader)
{
string magicString = reader.ReadString();
Debug.Assert(magicString == "CreatureBegin");
id = reader.ReadInt64();
pos = reader.ReadVector2();
viewAngle = reader.ReadSingle();
feelerAngle = reader.ReadSingle();
Energy = reader.ReadSingle();
age = reader.ReadSingle();
generation = reader.ReadInt32();
color = reader.ReadColor();
motherId = reader.ReadInt64();
int childrenCount = reader.ReadInt32();
childIds = new List <long>();
for (int childIndex = 0; childIndex < childrenCount; childIndex++)
{
childIds.Add(reader.ReadInt64());
}
brain = new NeuronalNetwork();
brain.Deserialize(reader);
SetupVariablesFromBrain();
}
/// <summary>
/// Initializes a new instance of the <see cref="NeuronalNetworkTrainPatterns"/> class.
/// </summary>
/// <param name="neuronalNetwork">The neuronal network.</param>
/// <param name="trainingSet">The training set.</param>
/// <param name="preferences">The preferences.</param>
/// <param name="trainingDataReady">A value indicating whether the training data is ready or not.</param>
/// <param name="eventStop">The event stop event.</param>
/// <param name="eventStopped">The event stopped event.</param>
/// <param name="mainForm">The main form.</param>
/// <param name="mutexes">The mutexes.</param>
public NeuronalNetworkTrainPatterns(
NeuronalNetwork neuronalNetwork,
NeuronalNetworkDatabase trainingSet,
Preferences preferences,
bool trainingDataReady,
ManualResetEvent eventStop,
ManualResetEvent eventStopped,
MainForm mainForm,
List <Mutex> mutexes)
{
this.CurrentPatternIndex = 0;
this.DataReady = trainingDataReady;
this.NeuronalNetwork = neuronalNetwork;
this.database = trainingSet;
this.Preferences = preferences;
this.mainForm = mainForm;
this.eventStop = eventStop;
this.eventStopped = eventStopped;
this.mutexes = mutexes;
this.recognitions = 0;
this.nextPattern = 0;
this.needHessian = true;
this.backProperties = 0;
this.dmse = 0;
this.neuronalNetworks = 0;
this.dmse200 = 0;
this.highPerformanceTimer = new HighPerformanceTimer();
this.GetGaussianKernel(this.Preferences.ElasticSigma);
}
public Creature(Creature mother, CreatureManager manager) :
this(manager)
{
id = currentId++;
motherId = mother.id;
generation = mother.generation + 1;
if (generation > manager.MaxGeneration)
{
manager.MaxGeneration = generation;
}
this.pos = mother.pos;
this.viewAngle = Simulation.RandomFloat() * Mathf.PI * 2;
this.brain = mother.brain.CloneFullMesh();
AmountOfMemory = mother.AmountOfMemory;
AmountOfHidden = mother.AmountOfHidden;
inMemory = new InputNeuron[AmountOfMemory];
outMemory = new WorkingNeuron[AmountOfMemory];
SetupFeelers(true, mother.AmountOfFeelers);
SetupVariablesFromBrain();
DoMutations(mother);
if (manager.SelectedCreature == null || manager.SelectedCreature.Energy < 100)
{
manager.SelectedCreature = this;
}
}
public void Initalzie(int poblationNum, int[] neuronalNetworkSize, int dinoStage)
{
infoLenght = neuronalNetworkSize[0];
poblation = new GameObject[poblationNum];
NeuronalList = new List <NeuronalNetwork>();
InfoDirector.Instance.SetDinos(poblationNum);
for (int i = 0; i < poblationNum; i++)
{
GameObject myDino = Instantiate(dinoPrefab);
NeuronalNetwork myIA = new NeuronalNetwork(neuronalNetworkSize);
NeuronalList.Add(myIA);
myDino.GetComponent <DinoBehaviour>().Reset(myIA, infoLenght);
myDino.transform.position = transform.position;
GameObject style = Instantiate(dinoStyle);
myDino.GetComponent <DinoBehaviour>().Rendering = true; //render all
myDino.GetComponent <DinoBehaviour>().DinoID = i;
style.GetComponent <AnimationBehaviour>().DinoStage = dinoStage;
style.transform.SetParent(myDino.transform);
if (dinoStage == 2)
{
GameObject proyectile = Instantiate(dinoProyectile);
proyectile.transform.SetParent(myDino.transform);
}
poblation[i] = myDino;
myDino.transform.SetParent(transform);
}
TryToLoad(poblationNum, neuronalNetworkSize);
}
public Creature(Vector2 pos, float viewAngle)
{
id = currentId++;
this.pos = pos;
this.viewAngle = viewAngle;
inBias.SetName(NAME_IN_BIAS);
inFoodValuePosition.SetName(NAME_IN_FOODVALUEPOSITION);
inFoodValueFeeler.SetName(NAME_IN_FOODVALUEFEELER);
inOcclusionFeeler.SetName(NAME_IN_OCCLUSIONFEELER);
inEnergy.SetName(NAME_IN_ENERGY);
inAge.SetName(NAME_IN_AGE);
inGeneticDifference.SetName(NAME_IN_GENETICDIFFERENCE);
inWasAttacked.SetName(NAME_IN_WASATTACKED);
inWaterOnFeeler.SetName(NAME_IN_WATERONFEELER);
inWaterOnCreature.SetName(NAME_IN_WATERONCREATURE);
inMemory1.SetName(NAME_IN_MEMORY1);
outBirth.SetName(NAME_OUT_BIRTH);
outRotate.SetName(NAME_OUT_ROTATE);
outForward.SetName(NAME_OUT_FORWARD);
outFeelerAngle.SetName(NAME_OUT_FEELERANGLE);
outAttack.SetName(NAME_OUT_ATTACK);
outEat.SetName(NAME_OUT_EAT);
outMemory1.SetName(NAME_OUT_MEMORY1);
brain = new NeuronalNetwork();
brain.AddInputNeuron(inBias);
brain.AddInputNeuron(inFoodValuePosition);
brain.AddInputNeuron(inFoodValueFeeler);
brain.AddInputNeuron(inOcclusionFeeler);
brain.AddInputNeuron(inEnergy);
brain.AddInputNeuron(inAge);
brain.AddInputNeuron(inGeneticDifference);
brain.AddInputNeuron(inWasAttacked);
brain.AddInputNeuron(inWaterOnFeeler);
brain.AddInputNeuron(inWaterOnCreature);
brain.AddInputNeuron(inMemory1);
brain.GenerateHiddenNeurons(10);
brain.AddOutputNeuron(outBirth);
brain.AddOutputNeuron(outRotate);
brain.AddOutputNeuron(outForward);
brain.AddOutputNeuron(outFeelerAngle);
brain.AddOutputNeuron(outAttack);
brain.AddOutputNeuron(outEat);
brain.AddOutputNeuron(outMemory1);
brain.GenerateFullMesh();
brain.RandomizeAllWeights();
CalculateFeelerPos(MAXIMUMFEELERDISTANCE);
color = new Color(EvoGame.RandomFloat(), EvoGame.RandomFloat(), EvoGame.RandomFloat());
GenerateColorInv();
CalculateCollisionGridPos();
}
public Creature(Vector2 pos, float viewAngle)
{
if (spriteBatch == null)
{
spriteBatch = new SpriteBatch(EvoGame.Instance.GraphicsDevice);
bodyTex = EvoGame.Instance.Content.Load <Texture2D>("Map/SandTexture");
feelerTex = EvoGame.Instance.Content.Load <Texture2D>("Map/SandTexture");
}
this.pos = pos;
this.viewAngle = viewAngle;
inBias.SetName(NAME_IN_BIAS);
inFoodValuePosition.SetName(NAME_IN_FOODVALUEPOSITION);
inFoodValueFeeler.SetName(NAME_IN_FOODVALUEFEELER);
inOcclusionFeeler.SetName(NAME_IN_OCCLUSIONFEELER);
inEnergy.SetName(NAME_IN_ENERGY);
inAge.SetName(NAME_IN_AGE);
inGeneticDifference.SetName(NAME_IN_GENETICDIFFERENCE);
inWasAttacked.SetName(NAME_IN_WASATTACKED);
inWaterOnFeeler.SetName(NAME_IN_WATERONFEELER);
inWaterOnCreature.SetName(NAME_IN_WATERONCREATURE);
outBirth.SetName(NAME_OUT_BIRTH);
outRotate.SetName(NAME_OUT_ROTATE);
outForward.SetName(NAME_OUT_FORWARD);
outFeelerAngle.SetName(NAME_OUT_FEELERANGLE);
outAttack.SetName(NAME_OUT_ATTACK);
outEat.SetName(NAME_OUT_EAT);
brain = new NeuronalNetwork();
brain.AddInputNeuron(inBias);
brain.AddInputNeuron(inFoodValuePosition);
brain.AddInputNeuron(inFoodValueFeeler);
brain.AddInputNeuron(inOcclusionFeeler);
brain.AddInputNeuron(inEnergy);
brain.AddInputNeuron(inAge);
brain.AddInputNeuron(inGeneticDifference);
brain.AddInputNeuron(inWasAttacked);
brain.AddInputNeuron(inWaterOnFeeler);
brain.AddInputNeuron(inWaterOnCreature);
brain.GenerateHiddenNeurons(10);
brain.AddOutputNeuron(outBirth);
brain.AddOutputNeuron(outRotate);
brain.AddOutputNeuron(outForward);
brain.AddOutputNeuron(outFeelerAngle);
brain.AddOutputNeuron(outAttack);
brain.AddOutputNeuron(outEat);
brain.GenerateFullMesh();
brain.RandomizeAllWeights();
CalculateFeelerPos();
color = new Color((float)EvoGame.GlobalRandom.NextDouble(), (float)EvoGame.GlobalRandom.NextDouble(), (float)EvoGame.GlobalRandom.NextDouble());
}
static void SimpleTest()
{
var neuralNetwork = new NeuronalNetwork();
var network = new SimpleNetwork(neuralNetwork, Sigmoid, Sigmoid);
var layers = new int[5];
layers[0] = 2;
layers[1] = 3;
layers[2] = 5;
layers[3] = 4;
layers[4] = 3;
network.Init(layers);
Console.WriteLine($"Created Network with {layers[0]} input neurons and {layers[layers.Length-1]} output neurons.");
var consoleInput = string.Empty;
var stopWatch = new Stopwatch();
do
{
Console.WriteLine("Please enter all input values:");
for (var i = 0; i < layers[0]; i++)
{
Console.Write($"{i}. > ");
consoleInput = Console.ReadLine();
if (double.TryParse(consoleInput, out var value))
{
network.SetInputValue(i, value);
}
}
Console.WriteLine("Process..");
stopWatch.Reset();
stopWatch.Start();
network.Process();
stopWatch.Stop();
Console.WriteLine($"Finished! Time: {stopWatch.ElapsedTicks} Ticks ({stopWatch.ElapsedMilliseconds} ms)");
Console.WriteLine("Output values:");
for (var i = 0; i < layers[layers.Length - 1]; i++)
{
Console.WriteLine($"{i}.: {network.GetOutputValue(i)}");
}
Console.Write("Enter anything to exit.");
consoleInput = Console.ReadLine();
} while (consoleInput == string.Empty);
}
public NeuronalNetwork(NeuronalNetwork aSource)
{
input = new NeuronLayer(aSource.input);
output = new NeuronLayer(aSource.output);
var last = input;
for (int i = 0; i < aSource.layers.Count; i++)
{
var layer = new NeuronLayer(aSource.layers[i]);
layers.Add(layer);
layer.InitNeurons(last, aSource.layers[i]);
last = layer;
}
output.InitNeurons(last, aSource.output);
}
public Creature(Creature mother)
{
this.pos = mother.pos;
this.viewAngle = (float)EvoGame.GlobalRandom.NextDouble() * Mathf.PI * 2;
this.brain = mother.brain.CloneFullMesh();
inBias = brain.GetInputNeuronFromName(NAME_IN_BIAS);
inFoodValuePosition = brain.GetInputNeuronFromName(NAME_IN_FOODVALUEPOSITION);
inFoodValueFeeler = brain.GetInputNeuronFromName(NAME_IN_FOODVALUEFEELER);
inOcclusionFeeler = brain.GetInputNeuronFromName(NAME_IN_OCCLUSIONFEELER);
inEnergy = brain.GetInputNeuronFromName(NAME_IN_ENERGY);
inAge = brain.GetInputNeuronFromName(NAME_IN_AGE);
inGeneticDifference = brain.GetInputNeuronFromName(NAME_IN_GENETICDIFFERENCE);
inWasAttacked = brain.GetInputNeuronFromName(NAME_IN_WASATTACKED);
inWaterOnFeeler = brain.GetInputNeuronFromName(NAME_IN_WATERONFEELER);
inWaterOnCreature = brain.GetInputNeuronFromName(NAME_IN_WATERONCREATURE);
outBirth = brain.GetOutputNeuronFromName(NAME_OUT_BIRTH);
outRotate = brain.GetOutputNeuronFromName(NAME_OUT_ROTATE);
outForward = brain.GetOutputNeuronFromName(NAME_OUT_FORWARD);
outFeelerAngle = brain.GetOutputNeuronFromName(NAME_OUT_FEELERANGLE);
outAttack = brain.GetOutputNeuronFromName(NAME_OUT_ATTACK);
outEat = brain.GetOutputNeuronFromName(NAME_OUT_EAT);
CalculateFeelerPos();
for (int i = 0; i < 10; i++)
{
brain.RandomMutation(0.1f);
}
float r = mother.color.R / 255f;
float g = mother.color.G / 255f;
float b = mother.color.B / 255f;
r += (float)EvoGame.GlobalRandom.NextDouble() * 0.1f - 0.05f;
g += (float)EvoGame.GlobalRandom.NextDouble() * 0.1f - 0.05f;
b += (float)EvoGame.GlobalRandom.NextDouble() * 0.1f - 0.05f;
r = Mathf.Clamp01(r);
g = Mathf.Clamp01(g);
b = Mathf.Clamp01(b);
color = new Color(r, g, b);
}
static void BasicTest()
{
var inputNeuron = new InputNeuron();
var calcNeuron1 = new FunctionNeuronProcess(ds => ds * 2);
var calcNeuron2 = new FunctionNeuronProcess(ds => ds * 2);
var outputNeuron = new OutputNeuron(ds => ds * 2);
var network = new NeuronalNetwork();
network.AddNeuron(inputNeuron);
network.AddNeuron(calcNeuron1);
network.AddNeuron(calcNeuron2);
network.AddNeuron(outputNeuron);
var synapse11 = network.CreateSynapse(inputNeuron, calcNeuron1);
var synapse12 = network.CreateSynapse(inputNeuron, calcNeuron2);
var synapse21 = network.CreateSynapse(calcNeuron1, outputNeuron);
var synapse22 = network.CreateSynapse(calcNeuron2, outputNeuron);
synapse11.Weight = 2;
synapse12.Weight = 2;
synapse21.Weight = 2;
synapse22.Weight = 2;
Console.WriteLine("Write any Value");
var input = string.Empty;
do
{
network.Reset();
Console.Write("> ");
input = Console.ReadLine();
if (double.TryParse(input, out double value))
{
inputNeuron.Value = value;
Console.Write("Calculating..");
network.FeedForward();
Console.WriteLine("Finished. Result: " + outputNeuron.Value);
}
} while (input != string.Empty);
}
public void NewGeneration()
{
generation++;
for (int i = 0; i < poblation.Length; i++)
{
poblation[i].GetComponent <DinoBehaviour>().CalculateFitness();
}
NeuronalList.Sort();
for (int i = 0; i < poblation.Length / 2; i++)
{
NeuronalList[poblation.Length - 1 - i] = new NeuronalNetwork(NeuronalList[i]);
NeuronalList[i] = new NeuronalNetwork(NeuronalList[i]);
NeuronalList[poblation.Length - 1 - i].Mutar();
}
for (int i = 0; i < poblation.Length; i++)
{
poblation[i].GetComponent <DinoBehaviour>().Reset(NeuronalList[i], infoLenght);
}
}
public Creature(Creature mother)
{
id = currentId++;
//this.mother = mother;
generation = mother.generation + 1;
if (generation > _maximumGeneration)
{
_maximumGeneration = generation;
}
this.pos = mother.pos;
this.viewAngle = EvoGame.RandomFloat() * Mathf.PI * 2;
this.brain = mother.brain.CloneFullMesh();
SetupVariablesFromBrain();
CalculateFeelerPos(MAXIMUMFEELERDISTANCE);
for (int i = 0; i < 10; i++)
{
brain.RandomMutation(0.1f);
}
int r = mother.color.R;
int g = mother.color.G;
int b = mother.color.B;
r += EvoGame.RandomInt(-5, 6);
g += EvoGame.RandomInt(-5, 6);
b += EvoGame.RandomInt(-5, 6);
r = Mathf.ClampColorValue(r);
g = Mathf.ClampColorValue(g);
b = Mathf.ClampColorValue(b);
color = new Color(r, g, b);
GenerateColorInv();
if (CreatureManager.SelectedCreature == null || CreatureManager.SelectedCreature.Energy < 100)
{
CreatureManager.SelectedCreature = this;
}
}
void Start()
{
poblation = new GameObject[poblationNum];
NeuronalList = new List <NeuronalNetwork>();
for (int i = 0; i < poblationNum; i++)
{
GameObject myShip = Instantiate(shipPrefab);
NeuronalNetwork myIA = new NeuronalNetwork(neuronalNetworkSize);
NeuronalList.Add(myIA);
myShip.GetComponent <ShipMovement>().ReciveNeuronalNetwork(myIA);
myShip.GetComponent <ShipMovement>().SetGoal(goal.transform);
myShip.transform.position = transform.position;
poblation[i] = myShip;
}
poblation[0].name = "Pro";
poblation[0].transform.GetChild(0).GetComponent <MeshRenderer>().material.color = Color.cyan;
poblation[0].transform.GetChild(1).GetComponent <MeshRenderer>().material.color = Color.white;
poblation[0].transform.GetChild(2).GetComponent <MeshRenderer>().material.color = Color.yellow;
poblation[0].transform.GetChild(3).GetComponent <MeshRenderer>().material.color = Color.yellow;
}
private void NewGeneration()
{
generation++;
for (int i = 0; i < poblationNum; i++)
{
poblation[i].GetComponent <ShipMovement>().CalculateFitness();
}
NeuronalList.Sort();
for (int i = 0; i < poblationNum / 2; i++)
{
NeuronalList[poblationNum - 1 - i] = new NeuronalNetwork(NeuronalList[i]);
NeuronalList[i] = new NeuronalNetwork(NeuronalList[i]);
NeuronalList[poblationNum - 1 - i].Mutar();
}
for (int i = 0; i < poblationNum; i++)
{
poblation[i].GetComponent <ShipMovement>().ReciveNeuronalNetwork(NeuronalList[i]);
poblation[i].transform.position = transform.position;
poblation[i].transform.rotation = transform.rotation;
}
}
public void Reset(NeuronalNetwork neuNet, int infoLeng)
{
myNeuronalNetwork = neuNet;
infoLentght = infoLeng;
alive = true;
actionTime = 0;
infoInstance.ReviveDino(dinoID);
fitness = 0;
crouching = false;
pos = new Vector3(0, 0, 0);
transform.position = pos;
if (act != null)
{
CleanDelegate();
act += Think;
}
if (rendering)
{
GetComponentInChildren <AnimationBehaviour>().ReturnToIdle();
}
gameObject.SetActive(true);
}
public Creature(Creature mother, CreatureManager manager) :
this(manager)
{
id = currentId++;
//this.mother = mother;
generation = mother.generation + 1;
if (generation > _maximumGeneration)
{
_maximumGeneration = generation;
}
this.pos = mother.pos;
this.viewAngle = Simulation.RandomFloat() * Mathf.PI * 2;
this.brain = mother.brain.CloneFullMesh();
AmountOfMemory = mother.AmountOfMemory;
inMemory = new InputNeuron[AmountOfMemory];
outMemory = new WorkingNeuron[AmountOfMemory];
SetupVariablesFromBrain();
CalculateFeelerPos(MAXIMUMFEELERDISTANCE);
if (Simulation.RandomFloat() > 0.01f)
{
MutateConnections();
}
else
{
MutateMemory();
}
MutateColor(mother);
GenerateColorInv();
if (manager.SelectedCreature == null || manager.SelectedCreature.Energy < 100)
{
manager.SelectedCreature = this;
}
}
public Creature(Creature mother, Creature father, CreatureManager manager) :
this(manager)
{
id = currentId++;
motherId = mother.id;
generation = mother.generation + 1;
if (generation > manager.MaxGeneration)
{
manager.MaxGeneration = generation;
}
pos = mother.pos;
viewAngle = Simulation.RandomFloat() * Mathf.PI * 2;
if (Simulation.SimulationConfiguration.MateBrainPercentage == 1.0f)
{
brain = father.brain.CloneFullMesh();
}
else
{
brain = mother.brain.CloneFullMesh();
brain.MixNetwork(father.brain, Simulation.SimulationConfiguration.MateBrainPercentage);
}
AmountOfMemory = mother.AmountOfMemory;
AmountOfHidden = mother.AmountOfHidden;
inMemory = new InputNeuron[AmountOfMemory];
outMemory = new WorkingNeuron[AmountOfMemory];
SetupFeelers(true, mother.AmountOfFeelers);
SetupVariablesFromBrain();
DoMutations(mother);
if (manager.SelectedCreature == null || manager.SelectedCreature.Energy <= 100)
{
manager.SelectedCreature = this;
}
}
void Awake()
{
_brain = new NeuronalNetwork(inputs, outputs, hiddenLayers, neuronsPerLayer, linearGrade, bias);
_brain.CreateNet();
_genome = _brain.GetWeights();
}
//Public things
public void DyingWormsLastWishes(NeuronalNetwork controller, float Fitness, Worm wormtoremove, int foodeaten, Color wormcolor, bool IsCannibal)
{
//Add worm controller to best list
if (IsCannibal == false)
{
ListOfBestWormBrains.Add(new WormList(Fitness, controller, foodeaten, wormcolor));
NumberOfAliveWorms--;
//Sort list from best to worst
if (ListOfBestWormBrains.Count > 2)
{
ListOfBestWormBrains.Sort(delegate(WormList b1, WormList b2) { return(b1.Fitness.CompareTo(b2.Fitness)); });
ListOfBestWormBrains.Reverse();
}
if (ListOfBestWormBrains.Count > 100)
{
ListOfBestWormBrains.RemoveAt(ListOfBestWormBrains.Count - 1); //Keep 100 best brains in safe;
}
}
//Add best worm eater controller to list containing the best ones
if (IsCannibal == true)
{
ListOfBestWormEaterBrains.Add(new WormList(Fitness, controller, foodeaten, wormcolor));
if (ListOfBestWormEaterBrains.Count > 2)
{
ListOfBestWormEaterBrains.Sort(delegate(WormList b1, WormList b2) { return(b1.Fitness.CompareTo(b2.Fitness)); });
ListOfBestWormEaterBrains.Reverse();
}
if (ListOfBestWormEaterBrains.Count > 100)
{
ListOfBestWormEaterBrains.RemoveAt(ListOfBestWormEaterBrains.Count - 1); //Keep 100 best brains in safe;
}
}
//Do the things to keep worms alive
if (UseGenerations == false && IsCannibal == false)
{
NumberOfWormsAliveAfterExtinction++;
if (foodeaten >= 4)
{
int NumberToSpawn = foodeaten / 4;
//if (NumberToSpawn > 4) NumberToSpawn = 4;
//print(NumberToSpawn);
if (NumberOfAliveWorms <= AmountOfWorms)
{
for (int i = 0; i < NumberToSpawn; i++)
{
NumberOfAliveWorms++;
GenerateWorms(1);
controller.Mutate(1);
ListOfWorms[ListOfWorms.Count - 1].GetComponent <Worm>().SetNeuralNetwork(controller, wormcolor);
}
}
}
ListOfWorms.Remove(wormtoremove.gameObject);
Destroy(wormtoremove.gameObject);
}
//Do things to keep wormeaters alive
if (UseGenerations == false && IsCannibal == true)
{
NumberOfWormEatersAliveAfterExtinction++;
if (foodeaten >= 2)
{
int NumberToSpawn = foodeaten / 2;
//if (NumberToSpawn > 3) NumberToSpawn = 3;
//print(NumberToSpawn);
for (int i = 0; i < NumberToSpawn; i++)
{
//NumberOfAliveWorm
GenerateWormEaters(1);
controller.Mutate(1);
ListOfWormEaters[ListOfWormEaters.Count - 1].GetComponent <Worm>().SetNeuralNetwork(controller, wormcolor);
}
}
ListOfWormEaters.Remove(wormtoremove.gameObject);
Destroy(wormtoremove.gameObject);
}
}
//Install a brain
public void SetNeuralNetwork(NeuronalNetwork NewController, Color color)
{
Controller = new NeuronalNetwork(NewController);
IsControllerSet = true;
SetColor(color);
}
public Creature(Vector2 pos, float viewAngle, CreatureManager manager) :
this(manager)
{
id = currentId++;
this.pos = pos;
this.viewAngle = viewAngle;
inBias.SetName(NAME_IN_BIAS);
inFoodValuePosition.SetName(NAME_IN_FOODVALUEPOSITION);
inEnergy.SetName(NAME_IN_ENERGY);
inAge.SetName(NAME_IN_AGE);
inWasAttacked.SetName(NAME_IN_WASATTACKED);
inWaterOnCreature.SetName(NAME_IN_WATERONCREATURE);
//inOscilation .SetName(NAME_IN_OSCILATION);
inMemory = new InputNeuron[AmountOfMemory];
for (int i = 0; i < AmountOfMemory; i++)
{
inMemory[i] = new InputNeuron();
inMemory[i].SetName(NAME_IN_MEMORY + (i + 1));
}
outBirth.SetName(NAME_OUT_BIRTH);
outRotate.SetName(NAME_OUT_ROTATE);
outForward.SetName(NAME_OUT_FORWARD);
outStrafe.SetName(NAME_OUT_STRAFE);
outEat.SetName(NAME_OUT_EAT);
outMate_Age.SetName(NAME_OUT_MATE_AGE);
outMate_Energy.SetName(NAME_OUT_MATE_ENERGY);
outMate_Generation.SetName(NAME_OUT_MATE_GENERATION);
outMate_GeneticDifference.SetName(NAME_OUT_MATE_GENETICDIFFERENCE);
outMate_Age_Weight.SetName(NAME_OUT_MATE_AGE_WEIGHT);
outMate_Energy_Weight.SetName(NAME_OUT_MATE_ENERGY_WEIGHT);
outMate_Generation_Weight.SetName(NAME_OUT_MATE_GENERATION_WEIGHT);
outMate_GeneticDifference_Weight.SetName(NAME_OUT_MATE_GENETICDIFFERENCE_WEIGHT);
//outOscilation .SetName(NAME_OUT_OSCILATION);
outMemory = new WorkingNeuron[AmountOfMemory];
for (int i = 0; i < AmountOfMemory; i++)
{
outMemory[i] = new WorkingNeuron(-1);
outMemory[i].SetName(NAME_OUT_MEMORY + (i + 1));
}
brain = new NeuronalNetwork();
brain.AddInputNeuron(inBias);
brain.AddInputNeuron(inFoodValuePosition);
brain.AddInputNeuron(inEnergy);
brain.AddInputNeuron(inAge);
brain.AddInputNeuron(inWasAttacked);
brain.AddInputNeuron(inWaterOnCreature);
//brain.AddInputNeuron(inOscilation);
for (int i = 0; i < AmountOfMemory; i++)
{
brain.AddInputNeuron(inMemory[i]);
}
brain.GenerateHiddenNeurons(AmountOfHidden, manager.simulation.SimulationConfiguration.NumberOfStartNeuronLayers);
brain.AddOutputNeuron(outBirth);
brain.AddOutputNeuron(outRotate);
brain.AddOutputNeuron(outForward);
brain.AddOutputNeuron(outStrafe);
brain.AddOutputNeuron(outEat);
brain.AddOutputNeuron(outMate_Age);
brain.AddOutputNeuron(outMate_Energy);
brain.AddOutputNeuron(outMate_Generation);
brain.AddOutputNeuron(outMate_GeneticDifference);
brain.AddOutputNeuron(outMate_Age_Weight);
brain.AddOutputNeuron(outMate_Energy_Weight);
brain.AddOutputNeuron(outMate_Generation_Weight);
brain.AddOutputNeuron(outMate_GeneticDifference_Weight);
//brain.AddOutputNeuron(outOscilation);
for (int i = 0; i < AmountOfMemory; i++)
{
brain.AddOutputNeuron(outMemory[i]);
}
SetupFeelers(false, 1);
brain.GenerateFullMesh();
brain.RandomizeAllWeights();
Color = Color.FromFloat(Simulation.RandomFloat(), Simulation.RandomFloat(), Simulation.RandomFloat());
GenerateColorInv();
CalculateCollisionGridPos();
}
public Creature(Vector2 pos, float viewAngle, CreatureManager manager) :
this(manager)
{
id = currentId++;
this.pos = pos;
this.viewAngle = viewAngle;
inBias.SetName(NAME_IN_BIAS);
inFoodValuePosition.SetName(NAME_IN_FOODVALUEPOSITION);
inFoodValueFeeler.SetName(NAME_IN_FOODVALUEFEELER);
inOcclusionFeeler.SetName(NAME_IN_OCCLUSIONFEELER);
inEnergy.SetName(NAME_IN_ENERGY);
inAge.SetName(NAME_IN_AGE);
inGeneticDifference.SetName(NAME_IN_GENETICDIFFERENCE);
inWasAttacked.SetName(NAME_IN_WASATTACKED);
inWaterOnFeeler.SetName(NAME_IN_WATERONFEELER);
inWaterOnCreature.SetName(NAME_IN_WATERONCREATURE);
//inOscilation .SetName(NAME_IN_OSCILATION);
inMemory = new InputNeuron[AmountOfMemory];
for (int i = 0; i < AmountOfMemory; i++)
{
inMemory[i] = new InputNeuron();
inMemory[i].SetName(NAME_IN_MEMORY + (i + 1));
}
outBirth.SetName(NAME_OUT_BIRTH);
outRotate.SetName(NAME_OUT_ROTATE);
outForward.SetName(NAME_OUT_FORWARD);
outFeelerAngle.SetName(NAME_OUT_FEELERANGLE);
outAttack.SetName(NAME_OUT_ATTACK);
outEat.SetName(NAME_OUT_EAT);
//outOscilation .SetName(NAME_OUT_OSCILATION);
outMemory = new WorkingNeuron[AmountOfMemory];
for (int i = 0; i < AmountOfMemory; i++)
{
outMemory[i] = new WorkingNeuron();
outMemory[i].SetName(NAME_OUT_MEMORY + (i + 1));
}
brain = new NeuronalNetwork();
brain.AddInputNeuron(inBias);
brain.AddInputNeuron(inFoodValuePosition);
brain.AddInputNeuron(inFoodValueFeeler);
brain.AddInputNeuron(inOcclusionFeeler);
brain.AddInputNeuron(inEnergy);
brain.AddInputNeuron(inAge);
brain.AddInputNeuron(inGeneticDifference);
brain.AddInputNeuron(inWasAttacked);
brain.AddInputNeuron(inWaterOnFeeler);
brain.AddInputNeuron(inWaterOnCreature);
//brain.AddInputNeuron(inOscilation);
for (int i = 0; i < AmountOfMemory; i++)
{
brain.AddInputNeuron(inMemory[i]);
}
brain.GenerateHiddenNeurons(10);
brain.AddOutputNeuron(outBirth);
brain.AddOutputNeuron(outRotate);
brain.AddOutputNeuron(outForward);
brain.AddOutputNeuron(outFeelerAngle);
brain.AddOutputNeuron(outAttack);
brain.AddOutputNeuron(outEat);
//brain.AddOutputNeuron(outOscilation);
for (int i = 0; i < AmountOfMemory; i++)
{
brain.AddOutputNeuron(outMemory[i]);
}
brain.GenerateFullMesh();
brain.RandomizeAllWeights();
CalculateFeelerPos(MAXIMUMFEELERDISTANCE);
Color = new Color(Simulation.RandomFloat(), Simulation.RandomFloat(), Simulation.RandomFloat());
GenerateColorInv();
CalculateCollisionGridPos();
}
public void ReciveNeuronalNetwork(NeuronalNetwork neuNet)
{
myNeuronalNetwork = neuNet;
}
