void Split()
{
if (GameObject.FindGameObjectsWithTag("Cell").Length > 1000)
{
return;
}
GameObject child1 = Instantiate(PrefabSupplier.CellPrefabReference, transform.position, transform.rotation, transform.parent);
GameObject child2 = Instantiate(PrefabSupplier.CellPrefabReference, transform.position, transform.rotation, transform.parent);
child1.transform.rotation *= Quaternion.Euler(0, 0, genome[CellModeIndex].SplitAngle + genome[CellModeIndex].Child1Angle);
child2.transform.rotation *= Quaternion.Euler(0, 0, genome[CellModeIndex].SplitAngle + genome[CellModeIndex].Child2Angle);
Rigidbody2D child1physics = child1.GetComponent <Rigidbody2D>();
Rigidbody2D child2physics = child2.GetComponent <Rigidbody2D>();
Cell child1Data = child1.GetComponent <Cell>();
Cell child2Data = child2.GetComponent <Cell>();
child1Data.Mass = Mass / 2f;
child2Data.Mass = Mass / 2f;
child1Data.genome = genome.Clone();
child2Data.genome = genome.Clone();
child1Data.CellModeIndex = genome[CellModeIndex].Child1ModeIndex;
child2Data.CellModeIndex = genome[CellModeIndex].Child2ModeIndex;
Vector2 splitVelocity = new Vector2(-.3f, 0).Rotate(transform.eulerAngles.z + genome[CellModeIndex].SplitAngle);
child1physics.velocity = physics.velocity + splitVelocity;
child2physics.velocity = physics.velocity - splitVelocity;
//Component[] child1Components = child1.GetComponents<Component>();
//Component[] child2Components = child2.GetComponents<Component>();
if (genome[CellModeIndex].Child1KeepAdhesin)
{
ReBuildAdhesins(child1Data, genome[CellModeIndex].Child1Angle);
}
if (genome[CellModeIndex].Child2KeepAdhesin)
{
ReBuildAdhesins(child2Data, genome[CellModeIndex].Child2Angle);
}
if (genome[CellModeIndex].MakeAdhesin)
{
GameObject adhesin = Instantiate(PrefabSupplier.AdhesinPrefabReference);
adhesin.transform.SetParent(gameObject.transform.parent);
Adhesin adhesinData = adhesin.GetComponent <Adhesin>();
adhesinData.Cell1 = child1Data;
adhesinData.Cell2 = child2Data;
child1Data.AddAdhesin(adhesinData);
child2Data.AddAdhesin(adhesinData);
}
Alive = false;
Destroy(gameObject);
}
public Genome[] breed(Genome g1, Genome g2, int nbChildren)
{
Genome[] children = new Genome[nbChildren];
for (int i = 0; i < nbChildren; i++)
{
Genome g1Clone = g1.Clone();
List <double> g1Weights = g1Clone.getNeuralNetwork().getWeightsList();
List <double> g2Weights = g2.getNeuralNetwork().getWeightsList();
// Genetic Crossover
for (int j = 0; j < g2Weights.Count; j++)
{
if (MathHelpers.randomNumber() <= 0.5)
{
g1Weights [j] = g2Weights [j];
}
}
// Preform Mutations on random weights
for (int k = 0; k < g1Weights.Count; k++)
{
if (MathHelpers.randomNumber() <= NeuroEvolution.mutationRate)
{
g1Weights [k] += MathHelpers.randomNumber() * NeuroEvolution.mutationRange * 2 - NeuroEvolution.mutationRange;
}
}
g1Clone.getNeuralNetwork().setNeuronsAndWeights(g1Clone.getNeuralNetwork().getNumberOfNeuronsPerLayer(), g1Weights);
children [i] = g1Clone;
}
return(children);
}
public void EvaluateBestCreature()
{
List <Genome> scores = new List <Genome>();
foreach (List <Environment> tests in environments)
{
// Average score
float score = 0;
foreach (Environment environment in tests)
{
score += environment.evolvable.GetScore();
}
score /= tests.Count;
// Put in the scores
Genome genome = tests[0].evolvable.genome.Clone();
genome.score = score; // Updates with the average score
scores.Add(genome);
}
scores.Sort(
delegate(Genome a, Genome b)
{
return(b.score.CompareTo(a.score)); // Larger first
}
);
// Sorts the already existing genomes and extract the best one
history.bestGenomes.Sort(
delegate(Genome a, Genome b)
{
return(b.score.CompareTo(a.score)); // Larger first
}
);
Genome oldBest = history.bestGenomes[0].Clone();
history.bestGenomes.Clear();
for (int i = 0; i < keepTop; i++)
{
history.bestGenomes.Add(scores[i].Clone());
}
history.bestScore = history.bestGenomes[0].score;
history.generations.Add(history.bestGenomes[0].Clone());
// Add backs the best genome
history.bestGenomes.Add(oldBest.Clone());
// Best genome (overall best)
history.bestGenomes.Add(GetBestGenomeIn(history.generations));
// Best scores for gizmos draw
history.CalculateMinMaxScore();
}
public Genome SelectGenome()
{
Genome g = bestGenome.Clone();
float totalScore = 0;
foreach (Creature creature in oldCreatures)
{
float score = creature.GetScore();
//Debug.Log("score: " + score);
totalScore += score * score;
}
float rand = Random.Range(0, totalScore);
float currentScore = 0;
foreach (Creature creature in oldCreatures)
{
float score = creature.GetScore();
currentScore += score * score;
if (rand <= currentScore)
{
g = creature.genome.Clone();
Debug.Log(score);
//Debug.Log("Genome selected had score of " + score);
//Debug.Log("Percentage " + (score * score / totalScore) * 100);
break;
}
}
return(g);
}
private void CreateCreatures()
{
for (int i = 0; i < variationsPerGeneration; i++)
{
Genome genome = bestGenome.Clone();
int mutationNum = UnityEngine.Random.Range(minMutations, maxMutations + 1);
for (int j = 0; j < mutationNum; j++)
{
genome.Mutate();
}
Vector3 position = distance * i;
GameObject simulation = Instantiate(simulationPrefab, position, Quaternion.identity) as GameObject;
Creature creature = simulation.transform.Find("creature").GetComponent <Creature>();
creature.genome = genome;
creatures.Add(creature);
}
}
public static void UniformCrossover(Genome parent1, Genome parent2, out Genome offspring1, out Genome offspring2)
{
offspring1 = (Genome)parent1.Clone();
offspring2 = (Genome)parent2.Clone();
for (int i = 0; i < parent1.Length; i++)
{
float rnd = Helper.Next(1.0f);
offspring1[i] = rnd < CROSSOVER_PROBABILITY ? parent1[i] : parent2[i];
offspring2[i] = rnd < CROSSOVER_PROBABILITY ? parent2[i] : parent1[i];
}
}
public List <Environment> CreateEnvironments(Genome genome, int i)
{
// Variants
List <Environment> tests = new List <Environment>();
environments.Add(tests);
for (int t = 0; t < testsPerMutation; t++)
{
CreateEnvironment(genome.Clone(), i, t);
}
return(tests);
}
/// <summary>
/// Creates and returns a mutated version of this chromosome
/// </summary>
/// <param name="MutatePercentChance">The percentage chance that any given node in the chromosome will be modified</param>
/// <returns></returns>
public Chromosome Mutate(int MutatePercentChance)
{
var c = new Chromosome(Genome.Clone() as Node);
var nodes = c.Enumerate().ToList();
Trace.Write("Mutating: ");
foreach (var n in nodes)
{
if (Random.Next(100) < MutatePercentChance)
{
//can add a child
if (Random.Next(100) < MutateChanceAdd && nodes.Count < MutateMaxSize)
{
Trace.Write(" add ");
n.AddChild(CreateNode());
}
//can lose a child
if ((Random.Next(100) < MutateChanceLose && nodes.Count > MutateMinSize) || nodes.Count > MutateMaxSize)
{
Trace.Write(" rem ");
if (n.Children.Count > 0)
{
n.RemoveChild(n.Children[Random.Next(n.Children.Count)]);
}
}
//can change an action (this is like add and lose) or a functor
if (Random.Next(100) < MutateChanceMutate)
{
Trace.Write(" mut ");
var a = n as Action;
if (a != null)
{
Mutate(a);
}
else
{
var co = n as Conditional;
if (co != null)
{
Mutate(co);
}
}
//n.GetType().GetMethod("Mutate").Invoke(n, null);
}
}
}
Trace.WriteLine("");
return(c);
}
private Genome GetBestGenomeIn(List <Genome> list)
{
Genome best = list[0].Clone();
float bestScore = best.score;
foreach (Genome genome in list)
{
if (genome.score > bestScore)
{
best = genome.Clone();
bestScore = best.score;
}
}
return(best.Clone());
}
public void CopulateBestCreatures()
{
List <Genome> genomes = new List <Genome>();
for (int i = 0; i < sexed; i++)
{
Genome g1 = history.bestGenomes[Random.Range(0, history.bestGenomes.Count - 1)];
Genome g2 = history.bestGenomes[Random.Range(0, history.bestGenomes.Count - 1)];
Genome g3 = g1.Clone();
genomes.Add(Genome.Copulate(g1, g2));
}
history.bestGenomes.AddRange(genomes);
}
//crossover and mutate 2 pairs
List <Genome> repopulate(List <Creature> selected)
{
List <Genome> ret = new List <Genome>();
//List<Genome> pars = new List<Genome>();
int size = selected.Count;
while (selected.Count > 1)
{
int r1 = Random.Range(0, selected.Count);
int r2 = Random.Range(0, selected.Count);
while (r1 == r2)
{
r2 = Random.Range(0, selected.Count);
}
Genome p1 = selected[r1].genome.Clone();
Genome p2 = selected[r2].genome.Clone();
Genome[] children = Genome.crossover2Pnt(p1, p2);
Genome c1 = children[0];
Genome c2 = children[1];
c1.Mutate(mutateRate);
c2.Mutate(mutateRate);
ret.Add(p1); //pars.Add(p1);
ret.Add(p2); //pars.Add(p2);
ret.Add(c1);
ret.Add(c2);
selected.RemoveAt(r1);
if (r1 < r2)
{
r2--;
}
selected.RemoveAt(r2);
}
if (selected.Count == 1)
{
//int i = Random.Range(0, pars.Count);
Genome p = selected[0].genome.Clone();
Genome c = p.Clone();
c.Mutate(mutateRate);
ret.Add(p);
ret.Add(c);
}
return(ret);
}
public static Genome[] crossover(Genome a, Genome b)
{
Genome[] ret = new Genome[2];
int startI = Random.Range(0, 8);
Genome n1 = a.Clone();
Genome n2 = b.Clone();
for (int i = startI; i < 8 - startI; i++)
{
n1.genes[i] = b.genes[i];
n2.genes[i] = a.genes[i];
}
n1.applyGenes();
n2.applyGenes();
ret[0] = n1; ret[1] = n2;
return(ret);
}
public object Clone()
{
var c = new Chromosome(Genome.Clone() as Node);
return(c);
}
public override void AddedToContainer()
{
base.AddedToContainer();
var builder = new FieldBuilder();
builder.BuildSessionStart(this);
var genomeTemplatesComboBox = builder.AddComboBoxField("Genome: ");
genomeTemplatesComboBox.Items.AddRange(EditorData.GenomeTemplates.Select(s => s.TemplateName));
genomeTemplatesComboBox.Index = 0;
var annTemplatesComboBox = builder.AddComboBoxField("ANN: ");
annTemplatesComboBox.Items.AddRange(EditorData.ANNTemplates.Select(s => s.TemplateName));
annTemplatesComboBox.Index = 0;
var creatureTemplatesComboBox = builder.AddComboBoxField("Creature: ");
creatureTemplatesComboBox.Items.AddRange(EditorData.CreatureTemplates.Select(s => s.TemplateName));
creatureTemplatesComboBox.Index = 0;
var mutateCheckBox = builder.AddCheckBoxField("Mutate the genome: ");
var amountField = builder.AddIntegerField("Amount to add: ");
amountField.MinValue = 1;
builder.AddResizableButtonField("OK", delegate(object sender)
{
string name = genomeTemplatesComboBox.Items[genomeTemplatesComboBox.Index];
Genome genome = null;
foreach (var g in EditorData.GenomeTemplates)
{
if (g.TemplateName == name)
{
genome = g.Genome;
}
}
name = annTemplatesComboBox.Items[annTemplatesComboBox.Index];
INeuralNetChromosome ann = null;
foreach (var a in EditorData.ANNTemplates)
{
if (a.TemplateName == name)
{
ann = a.ANN;
}
}
name = creatureTemplatesComboBox.Items[creatureTemplatesComboBox.Index];
ICreature creature = null;
foreach (var c in EditorData.CreatureTemplates)
{
if (c.TemplateName == name)
{
creature = c.Creature;
}
}
for (int i = 0; i < amountField.Value; i++)
{
var clone = (ICreature)creature.Clone();
var cloneGenome = genome.Clone();
cloneGenome.SetNetChromosome(ann.Clone());
if (mutateCheckBox.Checked)
{
cloneGenome.Mutate();
}
clone.ImprintGenome(cloneGenome);
world.AddEntity(clone);
clone.Position = new EntityPosition(Globals.Random.Next(world.Width), Globals.Random.Next(world.Height));
}
});
builder.BuildSessionEnd();
X = (Parent.Width / 2) - (Width / 2);
Y = (Parent.Height / 2) - (Height / 2);
CanResizeFormVertically = false;
}
void OneTrainingIteration(int i, BackgroundWorker bw)
{
Genome clone = maxgenome;
bool merged = false;
bool commoned = false;
if (rand.Next(3) > 0 && otherparents.Count > 0)
{
Genome p = otherparents.Pop();
if (rand.Next(2) == 0 || otherparents.Count < 1)
{
if (rand.Next(2) == 0 && otherparents.Count > 0)
{
Genome p2 = otherparents.Pop();
if (Genome.Merge(p, p2, out clone))
{
merged = true;
}
}
else
{
if (Genome.Merge(maxgenome, p, out clone))
{
merged = true;
}
}
}
else
{
Console.WriteLine("Commoning attempt. {0}:{1} {2}:{3}", prevcommon.ID, Interface.GenomeExists(prevcommon.ID), p.ID, Interface.GenomeExists(p.ID));
if (Genome.GetCommon(prevcommon, p, out clone))
{
prevcommon = clone;
commoned = true;
merged = true;
}
else
{
Console.WriteLine("Commoning failed. {0}:{1} {2}:{3}", prevcommon.ID, Interface.GenomeExists(prevcommon.ID), p.ID, Interface.GenomeExists(p.ID));
}
}
}
if (!merged)
{
clone = maxgenome.Clone();
int m = mutation * (i / 500 + 1) % 20;
clone.Mutate(m);
}
double[] output = clone.GetOutput(ogInput);
double errorcount = currentpuzzle.CheckDenormalisedValues(output, out string t);
//System.IO.File.WriteAllText("blep.txt", t);
double newscore = -errorcount;
string message = String.Format("{0}| Name: {1}; Score: {2}; {3}", i, clone.Name, newscore, commoned);
bw.ReportProgress(i, message);
if (newscore > maxscore)
{
otherparents.Clear();
genomechanged = true;
maxgenome = clone;
prevcommon = clone;
maxscore = newscore;
maxiteration = i;
string update = String.Format("{0}| Name: {1}; Score: {2};", i, maxgenome.Name, maxscore);
EmailAttempt("Sudokise Update: " + maxscore, update);
}
else if (newscore == maxscore && !merged)
{
otherparents.Push(clone);
}
else
{
DisposeGenome(clone);
}
}