public static float averageWeightDifference(Genome g1, Genome g2)
{
float g1TotalWeights = 0.0f;
float g2TotalWeights = 0.0f;
float matchingGeneCounter = 0.0f;
foreach (KeyValuePair <int, ConnectionGene> c in g1.getConnections())
{
if (g2.getConnections().ContainsKey(c.Key))
{
matchingGeneCounter++;
g1TotalWeights += c.Value.getWeight();
}
}
foreach (KeyValuePair <int, ConnectionGene> c in g2.getConnections())
{
if (g1.getConnections().ContainsKey(c.Key))
{
g2TotalWeights += c.Value.getWeight();
}
}
// Debug.Log("g1TotalWeights" + g1TotalWeights + "g2TotalWeights" + g1TotalWeights + "matchingGeneCounter" + matchingGeneCounter);
//Console.WriteLine("g1TotalWeights " + g1TotalWeights + " g2TotalWeights " + g1TotalWeights + " matchingGeneCounter " + matchingGeneCounter);
if (matchingGeneCounter == 0)
{
return(0f);
}
return((Math.Abs(g1TotalWeights - g2TotalWeights)) / matchingGeneCounter);
}
public static int excessCount(Genome g1, Genome g2)
{
int count = 0;
int g1HighestInnovation = g1.getConnections().Keys.Max();
int g2HighestInnovation = g2.getConnections().Keys.Max();
// if g1 has lower innovation, count excess genes on g2
if (g1HighestInnovation < g2HighestInnovation)
{
foreach (KeyValuePair <int, ConnectionGene> c in g2.getConnections())
{
if (c.Key > g1HighestInnovation)
{
count++;
}
}
}
else if (g1HighestInnovation > g2HighestInnovation)
{
foreach (KeyValuePair <int, ConnectionGene> c in g1.getConnections())
{
if (c.Key > g2HighestInnovation)
{
count++;
}
}
}
return(count);
}
public static int disjointCount(Genome g1, Genome g2)
{
int count = 0;
int g1HighestInnovation = g1.getConnections().Keys.Max();
int g2HighestInnovation = g2.getConnections().Keys.Max();
if (g1HighestInnovation <= g2HighestInnovation)
{
foreach (KeyValuePair <int, ConnectionGene> c in g1.getConnections())
{
if (!g2.getConnections().ContainsKey(c.Key))
{
count++;
}
}
foreach (KeyValuePair <int, ConnectionGene> c in g2.getConnections())
{
if (!g1.getConnections().ContainsKey(c.Key) && c.Key < g1HighestInnovation)
{
count++;
}
}
}
else if (g1HighestInnovation > g2HighestInnovation)
{
foreach (KeyValuePair <int, ConnectionGene> c in g2.getConnections())
{
if (!g1.getConnections().ContainsKey(c.Key))
{
count++;
}
}
foreach (KeyValuePair <int, ConnectionGene> c in g1.getConnections())
{
if (!g2.getConnections().ContainsKey(c.Key) && c.Key < g2HighestInnovation)
{
count++;
}
}
}
return(count);
}
// matching genes are inherited randomly, disjoint and excess (unmatching genes) genes are inherited from the more fit parent
// parent1 is the more fit parent
public static Genome crossover(Random random, Genome parent1, Genome parent2)
{
Genome offspring = new Genome();
/**
* NodeGene Crossover
*/
// add NodeGenes from parent1 (fittest parent) to the offspring
foreach (KeyValuePair <int, NodeGene> n in parent1.getNodes())
{
NodeGene oNode = new NodeGene(n.Value);
offspring.addNodeGene(oNode);
}
/**
* ConnectionGene Crossover
*/
foreach (KeyValuePair <int, ConnectionGene> p1Gene in parent1.getConnections())
{
// when parent connection genes match one must be inherited by the offspring randomly
if (parent2.getConnections().ContainsKey(p1Gene.Key))
{
if (random.Next(100) <= 50)
{
// takes a copy of parent2 gene
offspring.addConnectionGene(new ConnectionGene(parent2.getConnections()[p1Gene.Key]));
}
else
{
//takes a copy of parent1 gene
offspring.addConnectionGene(new ConnectionGene(p1Gene.Value));
}
}
else // if they don't match (disjoint or excess), copy from more fit parent
{
offspring.addConnectionGene(new ConnectionGene(p1Gene.Value));
}
}
return(offspring);
}
public static bool compatibilityDistance(Genome g1, Genome g2)
{
int normalize = 1;
int g1GeneCount = g1.getConnections().Count;
int g2GeneCount = g2.getConnections().Count;
// if either genome has more than 20 genes, change normalize
if (g1GeneCount >= GENE_THRESHOLD || g2GeneCount >= GENE_THRESHOLD)
{
//normalise is set to the length of the largest genome
normalize = Math.Max(g1GeneCount, g2GeneCount);
}
float cDistance = ((excessCount(g1, g2) * Utility.COEFFICIENT1) / normalize)
+ ((disjointCount(g1, g2) * Utility.COEFFICIENT2) / normalize)
+ (averageWeightDifference(g1, g2) * Utility.COEFFICIENT3);
return(cDistance <= Utility.COMPATIBILITY_THRESHOLD);
}
public static void Main(string[] args)
{
Random random = new Random();
Genome initialGenome = new Genome();
int node0 = initialGenome.getNodes().Count;
initialGenome.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node0));
int node1 = initialGenome.getNodes().Count;
initialGenome.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node1));
int node2 = initialGenome.getNodes().Count;
initialGenome.addNodeGene(new NodeGene(NodeGene.NodeType.OUTPUT, node2));
InnovationUtility.incrementGlobalInnovation();
initialGenome.addConnectionGene(new ConnectionGene(node0, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, InnovationUtility.getGlobalInnovation()));
InnovationUtility.incrementGlobalInnovation();
initialGenome.addConnectionGene(new ConnectionGene(node1, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, InnovationUtility.getGlobalInnovation()));
Genome initialGenome1 = new Genome();
node0 = initialGenome1.getNodes().Count;
initialGenome1.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node0));
node1 = initialGenome1.getNodes().Count;
initialGenome1.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node1));
node2 = initialGenome1.getNodes().Count;
initialGenome1.addNodeGene(new NodeGene(NodeGene.NodeType.OUTPUT, node2));
initialGenome1.addConnectionGene(new ConnectionGene(node0, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 1));
initialGenome1.addConnectionGene(new ConnectionGene(node1, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 2));
Genome initialGenome2 = new Genome();
node0 = initialGenome2.getNodes().Count;
initialGenome2.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node0));
node1 = initialGenome2.getNodes().Count;
initialGenome2.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node1));
node2 = initialGenome2.getNodes().Count;
initialGenome2.addNodeGene(new NodeGene(NodeGene.NodeType.OUTPUT, node2));
initialGenome2.addConnectionGene(new ConnectionGene(node0, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 1));
initialGenome2.addConnectionGene(new ConnectionGene(node1, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 2));
Genome initialGenome3 = new Genome();
node0 = initialGenome3.getNodes().Count;
initialGenome3.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node0));
node1 = initialGenome3.getNodes().Count;
initialGenome3.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node1));
node2 = initialGenome3.getNodes().Count;
initialGenome3.addNodeGene(new NodeGene(NodeGene.NodeType.OUTPUT, node2));
initialGenome3.addConnectionGene(new ConnectionGene(node0, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 1));
initialGenome3.addConnectionGene(new ConnectionGene(node1, node2, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 2));
// //-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
// Genome initialGenome2 = new Genome();
// node1 = initialGenome2.getNodes().Count;
// initialGenome2.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node1));
// node2 = initialGenome2.getNodes().Count;
// initialGenome2.addNodeGene(new NodeGene(NodeGene.NodeType.INPUT, node2));
// node3 = initialGenome2.getNodes().Count;
// initialGenome2.addNodeGene(new NodeGene(NodeGene.NodeType.OUTPUT, node3));
// InnovationUtility.incrementGlobalInnovation();
// initialGenome2.addConnectionGene(new ConnectionGene(node1, node3, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 1));
// InnovationUtility.incrementGlobalInnovation();
// initialGenome2.addConnectionGene(new ConnectionGene(node2, node3, Genome.getRandomFloatBetweenPoints(random, -1.0, 1.0), true, 2));
//-------------------------------------------------------------------
initialGenome.addNodeMutation(random);
initialGenome3.addNodeMutation(random);
Console.Write("initialGenome: ");
foreach (KeyValuePair <int, ConnectionGene> c in initialGenome.getConnections())
{
Console.Write("[" + c.Key + "]");
}
Console.Write("\n" + "initialGenome1: ");
foreach (KeyValuePair <int, ConnectionGene> c in initialGenome1.getConnections())
{
Console.Write("[" + c.Key + "]");
}
Console.Write("\n");
Console.WriteLine("disjoint: " + Speciation.disjointCount(initialGenome, initialGenome1));
Console.WriteLine("excess: " + Speciation.excessCount(initialGenome, initialGenome1));
Console.Write("\n");
GeneratePopulation population = new GeneratePopulation(4);
population.addGenomeToPopulation(new Genome(initialGenome));
population.addGenomeToPopulation(new Genome(initialGenome1));
population.addGenomeToPopulation(new Genome(initialGenome2));
population.addGenomeToPopulation(new Genome(initialGenome3));
for (int i = 0; i < 60; i++)
{
population.sortGenomesIntoSpecies(random);
population.addAdjustedFitness();
population.fillNextGeneration(random);
Console.WriteLine("\n Generation: " + i);
// foreach(Species s in population.getSpeciesList()) {
// Console.WriteLine("New Species ");
// foreach(Genome g in s.getGenomesList()) {
// Console.WriteLine("Genome fitness: " + g.getFitness());
// }
// }
}
//--------------------------------------------------------------------------------
// Console.WriteLine("Parent1");
// foreach(KeyValuePair<int, NodeGene> n in initialGenome.getNodes()) {
// Console.WriteLine("ID: " + n.Value.getNodeNumber() + " Layer: " + n.Value.getNodeType());
// }
// Console.Write("\n");
// foreach(KeyValuePair<int, ConnectionGene> c in initialGenome.getConnections()) {
// Console.WriteLine("In: " + c.Value.getIn() + " Out: " + c.Value.getOut() + " Innov: " + c.Value.getInnovationNumber() + " Enabled: " + c.Value.getEnabled() + " Weight: " + c.Value.getWeight());
// }
// Console.Write("\n");
// Console.WriteLine("Parent2");
// foreach(KeyValuePair<int, NodeGene> n in initialGenome2.getNodes()) {
// Console.WriteLine("ID: " + n.Value.getNodeNumber() + " Layer: " + n.Value.getNodeType());
// }
// Console.Write("\n");
// foreach(KeyValuePair<int, ConnectionGene> c in initialGenome2.getConnections()) {
// Console.WriteLine("In: " + c.Value.getIn() + " Out: " + c.Value.getOut() + " Innov: " + c.Value.getInnovationNumber() + " Enabled: " + c.Value.getEnabled() + " Weight: " + c.Value.getWeight());
// }
// Console.Write("\n");
// Genome child = Evolution.crossover(random, initialGenome, initialGenome2);
// Console.WriteLine("Child");
// foreach(KeyValuePair<int, NodeGene> n in child.getNodes()) {
// Console.WriteLine("ID: " + n.Value.getNodeNumber() + " Layer: " + n.Value.getNodeType());
// }
// Console.Write("\n");
// foreach(KeyValuePair<int, ConnectionGene> c in child.getConnections()) {
// Console.WriteLine("In: " + c.Value.getIn() + " Out: " + c.Value.getOut() + " Innov: " + c.Value.getInnovationNumber() + " Enabled: " + c.Value.getEnabled() + " Weight: " + c.Value.getWeight());
// }
//------------------------------------------------------------------------------------------------------------------------------------------------------------
// Console.WriteLine(Speciation.compatibilityDistance(initialGenome, initialGenome2));
//------------------------------------------------------------------------------------------------------------------------------------------------------------
// GeneratePopulation population = new GeneratePopulation(4);
// population.addGenomeToPopulation(new Genome(initialGenome));
// population.addGenomeToPopulation(new Genome(initialGenome1));
// population.addGenomeToPopulation(new Genome(initialGenome2));
// population.addGenomeToPopulation(new Genome(initialGenome3));
// GeneratePopulation population = new GeneratePopulation(50);
// for(int i = 0; i < population.getPopulationSize(); i++) {
// population.addGenomeToPopulation(new Genome(initialGenome));
// }
// print connection genes
// Console.WriteLine("CONNECTION GENES: ");
// foreach(ConnectionGene gene in initialGenome.connections) {
// Console.WriteLine("IN: " + gene.getIn() + " OUT: " + gene.getOut() + " WEIGHT: " + gene.getWeight() + " ENABLED: " + gene.getEnabled() + " INNO: " + gene.getInnovationNumber());
// }
// Console.WriteLine("\n");
// for(int i = 1; i < 20; i++) {
// bestGen = population.GenerateNextGeneration(random);
// Console.Write(" Generation: " + i);
// // Console.Write(", Species Count: " + population.getSpeciesList().Count);
// Console.Write(", Highest Fitness: " + population.getHighestScore() + "\n");
// }
}
public void Check_Connection_Weights()
{
Assert.AreEqual(-0.9f, genome.getConnections()[genome.getInnovationNumbers()[0]].getWeight());
}
public void Length_After_Connection_Mutation()
{
genome.addConnectionMutation(random);
Assert.AreEqual(6, genome.getConnections().Count);
}
