/// <summary>
/// Create the start genome
/// </summary>
private void SetStartGenome()
{
_nodeCounter = new GeneCounter(0);
_connectionCounter = new GeneCounter(0);
_startGenome = new Genome();
int amountPlayerInputs = PlayerController.GetAmountOfInputs(_levelViewWidht, _levelViewHeight);
List <NodeGene> tmpInputNodes = new List <NodeGene>();
//Crate input nodes
for (int i = 0; i < amountPlayerInputs; i++)
{
NodeGene node = new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.SIGMOID);
_startGenome.AddNodeGene(node);
tmpInputNodes.Add(node);
}
//Create output nodes
NodeGene outputNode1 = new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.OUTPUT, 1f, ActivationFunctionHelper.Function.SIGMOID);
NodeGene outputNode2 = new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.OUTPUT, 1f, ActivationFunctionHelper.Function.SIGMOID);
_startGenome.AddNodeGene(outputNode1);
_startGenome.AddNodeGene(outputNode2);
//Create connections
for (int i = 0; i < amountPlayerInputs; i++)
{
_startGenome.AddConnectionGene(new ConnectionGene(tmpInputNodes[i].ID, outputNode1.ID, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(tmpInputNodes[i].ID, outputNode2.ID, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
}
}
public static void Test4()
{
Genome genome = new Genome();
NeuralNetwork net;
float[] input;
float[] output;
string logs = "======================TEST 4===================================\n\n";
genome = new Genome();
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.INPUT, 0));
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.INPUT, 1));
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.INPUT, 2));
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, 3));
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 4));
genome.AddConnectionGene(new ConnectionGene(0, 4, 0.4f, true, 0));
genome.AddConnectionGene(new ConnectionGene(1, 4, 0.7f, true, 1));
genome.AddConnectionGene(new ConnectionGene(2, 4, 0.1f, true, 2));
genome.AddConnectionGene(new ConnectionGene(4, 3, 1f, true, 3));
net = new NeuralNetwork(genome, Neuron.ActivationType.SIGMOID, false);
input = new float[] { 0.5f, 0.75f, 0.90f };
for (int i = 0; i < 3; i++)
{
output = net.FeedForward(input);
logs += "output is of length=" + output.Length + " and has output[0]=" + output[0] + " expecting 0.9924\n";
}
Debug.Log(logs);
}
// Use this for initialization
void Start()
{
Genome parent3GenomeSimple = new Genome();
//Create the input nodes
parent3GenomeSimple.AddNodeGene(new NodeGene(1, NodeGeneType.INPUT, 0f));
parent3GenomeSimple.AddNodeGene(new NodeGene(2, NodeGeneType.INPUT, 0f));
parent3GenomeSimple.AddNodeGene(new NodeGene(3, NodeGeneType.INPUT, 0f));
//Create the output node
parent3GenomeSimple.AddNodeGene(new NodeGene(4, NodeGeneType.OUTPUT, 1f));
//Create connections
parent3GenomeSimple.AddConnectionGene(new ConnectionGene(1, 4, 1.0, true, 1));
parent3GenomeSimple.AddConnectionGene(new ConnectionGene(2, 4, 1.0, true, 2));
parent3GenomeSimple.AddConnectionGene(new ConnectionGene(3, 4, 1.0, true, 3));
//Init the connection gene counter with 11
connectionCounter = new GeneCounter(4);
nodeCounter = new GeneCounter(5);
manager.Callback = this;
manager.CreateInitialPopulation(parent3GenomeSimple, nodeCounter, connectionCounter, 100);
}
public Genome CreateNeuronFromID(int ID, Genome genome)
{
for (int i = 0; i < innovations.Count; i++)
{
if (innovations[i].percepID == ID)
{
genome.AddNodeGene(innovations[i].percepID, innovations[i].percepType, false, innovations[i].splitValues, Random.Range(-1, 1));
return(genome);
}
}
genome.AddNodeGene(0, NodeType.Hidden, false, Vector2.zero, Random.Range(-1, 1));
return(genome);
}
/// <summary>
/// Create the start genome
/// </summary>
private void SetStartGenome()
{
_nodeCounter = new GeneCounter(0);
_connectionCounter = new GeneCounter(0);
_startGenome = new Genome();
//5 input nodes + 1 bias node
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
//OutputNodes
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.OUTPUT, 1f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
_startGenome.AddNodeGene(new NodeGene(_nodeCounter.GetNewNumber(), NodeGeneType.OUTPUT, 1f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
//Add connections to first output nde
_startGenome.AddConnectionGene(new ConnectionGene(0, 6, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(1, 6, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(2, 6, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(3, 6, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(4, 6, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(5, 6, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
//Connection to second ouztputNode
_startGenome.AddConnectionGene(new ConnectionGene(0, 7, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(1, 7, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(2, 7, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(3, 7, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(4, 7, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
_startGenome.AddConnectionGene(new ConnectionGene(5, 7, Random.Range(-1f, 1f), true, _connectionCounter.GetNewNumber()));
}
public void CrossoverTest()
{
// Parent 1
Genome parent1 = new Genome();
for (int i = 0; i < 3; i++)
{
NodeGene node = new NodeGene(NodeGene.TYPE.INPUT, i + 1);
parent1.AddNodeGene(node);
}
parent1.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, 4));
parent1.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 5));
parent1.AddConnectionGene(new ConnectionGene(1, 4, 1f, true, 1));
parent1.AddConnectionGene(new ConnectionGene(2, 4, 1f, false, 2));
parent1.AddConnectionGene(new ConnectionGene(3, 4, 1f, true, 3));
parent1.AddConnectionGene(new ConnectionGene(2, 5, 1f, true, 4));
parent1.AddConnectionGene(new ConnectionGene(5, 4, 1f, true, 5));
parent1.AddConnectionGene(new ConnectionGene(1, 5, 1f, true, 8));
// Parent 2 (More Fit)
Genome parent2 = new Genome();
for (int i = 0; i < 3; i++)
{
NodeGene node = new NodeGene(NodeGene.TYPE.INPUT, i + 1);
parent2.AddNodeGene(node);
}
parent2.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, 4));
parent2.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 5));
parent2.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 6));
parent2.AddConnectionGene(new ConnectionGene(1, 4, 1f, true, 1));
parent2.AddConnectionGene(new ConnectionGene(2, 4, 1f, false, 2));
parent2.AddConnectionGene(new ConnectionGene(3, 4, 1f, true, 3));
parent2.AddConnectionGene(new ConnectionGene(2, 5, 1f, true, 4));
parent2.AddConnectionGene(new ConnectionGene(5, 4, 1f, false, 5));
parent2.AddConnectionGene(new ConnectionGene(5, 6, 1f, true, 6));
parent2.AddConnectionGene(new ConnectionGene(6, 4, 1f, true, 7));
parent2.AddConnectionGene(new ConnectionGene(3, 5, 1f, true, 9));
parent2.AddConnectionGene(new ConnectionGene(1, 6, 1f, true, 10));
// Crossover
Genome child = Genome.Crossover(parent2, parent1, new System.Random(), 0.75f);
// Return Results
Debug.Log(String.Format("PARENT 1\n{0}\n\nPARENT 2\n{1}\n\nCROSSOVER CHILD\n{2}", parent1.ToString(), parent2.ToString(), child.ToString()));
}
/// <summary>
/// Crossover of two parent genomes to procuce one child
/// </summary>
/// <param name="parent1">the more fit parent!</param>
/// <param name="parent2">the less fit parent</param>
/// <returns>the newly breed child genome</returns>
public static Genome CrossOver(Genome parent1, Genome parent2)
{
Genome childGenome = new Genome();
//Copy nodes of the more fit parent
foreach (NodeGene parent1Node in parent1.Nodes.Values)
{
childGenome.AddNodeGene(new NodeGene(parent1Node));
}
//Iterate through every connection
foreach (ConnectionGene parent1Connection in parent1.Connections.Values)
{
if (parent2.Connections.ContainsKey(parent1Connection.InnovationNumber))
{
//Matching genes
if (Random.Range(-1.0f, 1.0f) >= 0)
{
childGenome.AddConnectionGene(new ConnectionGene(parent1Connection));
}
else
{
childGenome.AddConnectionGene(new ConnectionGene(parent2.Connections[parent1Connection.InnovationNumber]));
}
}
else
{
//Distjoint or excess gene
childGenome.AddConnectionGene(new ConnectionGene(parent1Connection));
}
}
return(childGenome);
}
public void EvaluatorTestInit()
{
Genome genome = new Genome();
int n1 = _nodeInnovation.GetNewInnovationNumber();
int n2 = _nodeInnovation.GetNewInnovationNumber();
int n3 = _nodeInnovation.GetNewInnovationNumber();
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.INPUT, n1));
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.INPUT, n2));
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, n3));
int c1 = _connectionInnovation.GetNewInnovationNumber();
int c2 = _connectionInnovation.GetNewInnovationNumber();
genome.AddConnectionGene(new ConnectionGene(n1, n3, 0.5f, true, c1));
genome.AddConnectionGene(new ConnectionGene(n2, n3, 0.5f, true, c2));
_eval = new EvalutorTestEvaluator(_config, genome, _nodeInnovation, _connectionInnovation);
}
public Genome GetDeafultGenome()
{
Genome g = new Genome(gt);
for (int i = 0; i < genome.GetNodeGenes().Count; i++)
{
g.AddNodeGene(genome.GetNodeGenes()[i]);
}
return(g);
}
// Use this for initialization
void Start()
{
startingGenome = new Genome();
startingGenome.AddNodeGene(new NodeGene(0, NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
startingGenome.AddNodeGene(new NodeGene(1, NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
startingGenome.AddNodeGene(new NodeGene(2, NodeGeneType.INPUT, 0f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
startingGenome.AddNodeGene(new NodeGene(3, NodeGeneType.OUTPUT, 1f, ActivationFunctionHelper.Function.STEEPENED_SIGMOID));
startingGenome.AddConnectionGene(new ConnectionGene(0, 3, Random.Range(0f, 1f), true, 0));
startingGenome.AddConnectionGene(new ConnectionGene(1, 3, Random.Range(0f, 1f), true, 1));
startingGenome.AddConnectionGene(new ConnectionGene(2, 3, Random.Range(0f, 1f), true, 2));
//Nodes for a complete network
/*
* startingGenome.AddNodeGene(new NodeGene(4, NodeGeneType.HIDDEN, 0.5f));
* startingGenome.AddNodeGene(new NodeGene(5, NodeGeneType.HIDDEN, 0.5f));
*
* startingGenome.AddConnectionGene(new ConnectionGene(0, 4, Random.Range(0f, 1f), true, 0));
* startingGenome.AddConnectionGene(new ConnectionGene(0, 5, Random.Range(0f, 1f), true, 1));
* startingGenome.AddConnectionGene(new ConnectionGene(1, 4, Random.Range(0f, 1f), true, 2));
* startingGenome.AddConnectionGene(new ConnectionGene(1, 5, Random.Range(0f, 1f), true, 3));
*
* startingGenome.AddConnectionGene(new ConnectionGene(4, 3, Random.Range(0f, 1f), true, 4));
* startingGenome.AddConnectionGene(new ConnectionGene(5, 3, Random.Range(0f, 1f), true, 5));
*
* startingGenome.AddConnectionGene(new ConnectionGene(2, 3, Random.Range(0f, 1f), true, 6));
* startingGenome.AddConnectionGene(new ConnectionGene(2, 4, Random.Range(0f, 1f), true, 7));
* startingGenome.AddConnectionGene(new ConnectionGene(2, 5, Random.Range(0f, 1f), true, 8));
*/
result = new List <int>();
_manager = new PopulationManager();
_manager.Callback = this;
_manager.CreateInitialPopulation(startingGenome, new GeneCounter(6), new GeneCounter(9), 400, true);
}
void OnEnable() //set up inital nodes and connections
{
gt = new GeneTracker();
genome = new Genome(gt);
nodes = new List <NodeGene>();
species = new List <Species>();
for (int i = 0; i < inputSize; i++)
{
NodeGene nodeIn = new NodeGene(NodeGene.NODETYPE.INPUT, gt.NewId(), 0, false, NodeGene.ACTIVATION_FUNCTION.NULL);
nodes.Add(nodeIn);
genome.AddNodeGene(nodeIn.Copy());
}
for (int i = 0; i < outputSize; i++)
{
NodeGene nodeOut = new NodeGene(NodeGene.NODETYPE.OUTPUT, gt.NewId(), 1, true, outputActiationFunction);
nodes.Add(nodeOut);
genome.AddNodeGene(nodeOut.Copy());
}
connections = new List <ConnectionGene>();
for (int i = 0; i < inputSize; i++)
{
for (int i2 = 0; i2 < outputSize; i2++)
{
//Debug.Log(genome.GetNodeGenes()[i]);
ConnectionGene con = new ConnectionGene(genome.GetNodeGenes()[i], genome.GetNodeGenes()[inputSize + i2], gt.Innovate());
connections.Add(con.Copy());
}
}
for (int i = 0; i < connections.Count; i++)
{
//Debug.Log(connections[i]);
}
}
public static Genome Clone(Genome genome)
{
Genome child = new Genome();
foreach (NodeGene node in genome.GetNodeGenes().Values)
{
child.AddNodeGene(node.Clone());
}
foreach (ConnectionGene con in genome.GetConnectionGenes().Values)
{
child.AddConnectionGene(con.Clone());
}
return(child);
}
public Genome InitGenome()
{
Genome g1 = new Genome(gt);
for (int i = 0; i < inputSize + outputSize; i++)
{
NodeGene node = GetDeafultGenome().GetNodeGenes()[i].Copy();
if (node.GetNodeType() == NodeGene.NODETYPE.OUTPUT || node.GetNodeType() == NodeGene.NODETYPE.HIDDEN)
{
node.SetBias(Random.Range(-1.0f, 1.0f));
//node.SetBias(1.0f);
}
g1.AddNodeGene(node);
//g1.GetNodeGenes()[inputSize + i].SetBias(Random.Range(-1.0f, 1.0f));
}
for (int i = 0; i < startConnections; i++)//sample n connections
{
ConnectionGene con = connections[Random.Range(0, connections.Count)].Copy();
//ConnectionGene con = connections[i].Copy();
con.SetWeight(Random.Range(-weightRange, weightRange));
//con.SetWeight(1.0f);
int inId = con.GetInNode().GetId();
con.SetInNode(g1.GetNodeGenes()[inId]);
int outId = con.GetOutNode().GetId();
//Debug.Log(con.GetOutNode());
//Debug.Log(outId);
con.SetOutNode(g1.GetNodeGenes()[outId]);
g1.AddConnectionGene(con);
}
if (speciation)
{
InsertGenomeIntoSpecies(g1, species);
impf.StatsSpecies(species.Count);
}
genomes.Add(g1);
return(g1);
}
public static Genome Crossover(Genome parent1, Genome parent2)
{
Genome child = new Genome();
foreach (NodeGene parent1Node in parent1.GetNodeGenes().Values)
{
child.AddNodeGene(parent1Node.Clone());
}
foreach (ConnectionGene parent1Node in parent1.GetConnectionGenes().Values)
{
if (parent2.GetConnectionGenes().ContainsKey(parent1Node.innovation)) //matching gene
{
child.AddConnectionGene(Random.value < 0.5f ? parent1Node.Clone() : parent2.GetConnectionGenes()[parent1Node.innovation].Clone());
}
else
{
child.AddConnectionGene(parent1Node.Clone());
}
}
return(child);
}
public static void MutateAddNode(this Genome genome)
{
var connection = genome.ConnectionGenes.Values.Where(cg => cg.IsEnabled).GetRandomElement();
if (connection == null)
{
return;
}
var newNode = new NodeGene();
genome.AddNodeGene(newNode);
var newPreviousConnection = new ConnectionGene(connection.PreviousNodeId, newNode.Id, 1);
genome.AddConnectionGene(newPreviousConnection);
var newNextConnection = new ConnectionGene(newNode.Id, connection.NextNodeId, connection.Weight);
genome.AddConnectionGene(newNextConnection);
connection.Toggle(false);
}
public static Genome Crossover(Genome parent1, Genome parent2)
{ // parent1 always more fit parent - no equal fitness parents
System.Random rand = new System.Random();
Genome offspring = new Genome();
foreach (NodeGene parent1Node in parent1.GetNodes().Values)
{
offspring.AddNodeGene(parent1Node.CopyNode());
}
foreach (ConnectionGene parent1Connection in parent1.GetConnections().Values)
{
if (parent2.GetConnections().ContainsKey(parent1Connection.getInnovation()))
{
offspring.AddConnectionGene((rand.NextDouble() > 0.5) ? parent1Connection.CopyConnection() : parent2.GetConnections()[parent1Connection.getInnovation()].CopyConnection());
}
else
{
offspring.AddConnectionGene(parent1Connection.CopyConnection());
}
}
return(offspring);
}
public Genome Copy()
{
Genome g = new Genome(track);
List <NodeGene> nodesList = new List <NodeGene>();
for (int i = 0; i < nodes.Count; i++)
{
nodesList.Add(nodes[i].Copy());
g.AddNodeGene(nodesList[i]);
}
List <ConnectionGene> connectionsList = new List <ConnectionGene>();
for (int i = 0; i < connections.Count; i++)
{
connectionsList.Add(connections[i].Copy());
connectionsList[i].SetInNode(g.FindNode(connections[i].GetInNode().GetId()));
connectionsList[i].SetOutNode(g.FindNode(connections[i].GetOutNode().GetId()));
//Debug.Log(connectionsList[i]);
g.AddConnectionGene(connectionsList[i]);
}
g.SetLayers(layers);
return(g);
}
public Genome CrossoverGenes(Genome genome1, Genome genome2, GeneTracker track)
{
Genome child = new Genome(track);
List <NodeGene> newNodeGenes = new List <NodeGene>();
//for (int i = 0; i < genome1.GetNodeGenes().Count; i++)
//{
// commonNodeGenes.Add(genome1.GetNodeGenes()[i].Copy());
//}
//for (int i = 0; i < genome2.GetNodeGenes().Count; i++)
//{
// if (!commonNodeGenes.Contains(genome2.GetNodeGenes()[i]))
// {
// commonNodeGenes.Add(genome2.GetNodeGenes()[i].Copy());
// }
//}
if (genome1.GetFitness() < genome2.GetFitness())
{//swap so genome1 has the higher fitness
Genome temp = genome2;
genome2 = genome1;
genome1 = temp;
}
//Debug.Log("g1 "+genome1+ "\ng2 " + genome2);
child.SetLayers(genome1.GetLayers());
/*
* for (int i = 0; i < genome1.GetNodeGenes().Count; i++) {
* for (int i2 = 0; i2 < genome2.GetNodeGenes().Count; i2++)
* {
*
*
* }
* }
*/
for (int i = 0; i < genome1.GetNodeGenes().Count; i++)
{
newNodeGenes.Add(genome1.GetNodeGenes()[i].Copy());
}
for (int i = 0; i < genome2.GetNodeGenes().Count; i++)
{
if (newNodeGenes.Contains(genome2.GetNodeGenes()[i]))
{
if (Random.Range(0, 2) == 1)
{
// newNodeGenes.RemoveAt(newNodeGenes.IndexOf(genome2.GetNodeGenes()[i]));
//newNodeGenes.Add(genome2.GetNodeGenes()[i].Copy());
newNodeGenes[newNodeGenes.IndexOf(genome2.GetNodeGenes()[i])].SetBias(genome2.GetNodeGenes()[i].GetBias());
}
}
}
for (int i = 0; i < genome1.GetNodeGenes().Count; i++)
{
child.AddNodeGene(newNodeGenes[i]);
}
List <ConnectionGene> newConnectionGenes = new List <ConnectionGene>();
//if equal choose random
for (int i = 0; i < genome1.GetConnectionGenes().Count; i++) //copy all connections
{
newConnectionGenes.Add(genome1.GetConnectionGenes()[i].Copy());
newConnectionGenes[i].SetInNode(child.FindNode(genome1.GetConnectionGenes()[i].GetInNode().GetId()));
newConnectionGenes[i].SetOutNode(child.FindNode(genome1.GetConnectionGenes()[i].GetOutNode().GetId()));
}
for (int i = 0; i < genome2.GetConnectionGenes().Count; i++)
{
//Debug.Log(newConnectionGenes.Contains(genome2.GetConnectionGenes()[i]));
if (newConnectionGenes.Contains(genome2.GetConnectionGenes()[i]))
{
//Debug.Log(Random.Range(0, 2) );
if (Random.Range(0, 2) == 1)
{
//newConnectionGenes.RemoveAt(newConnectionGenes.IndexOf(genome2.GetConnectionGenes()[i]));
//newConnectionGenes.Add(genome2.GetConnectionGenes()[i].Copy());
//newConnectionGenes[i].SetWeight(genome2.GetConnectionGenes()[i].GetWeight());
//Debug.Log(newConnectionGenes[newConnectionGenes.IndexOf(genome2.GetConnectionGenes()[i])].GetWeight());
newConnectionGenes[newConnectionGenes.IndexOf(genome2.GetConnectionGenes()[i])].SetWeight(genome2.GetConnectionGenes()[i].GetWeight());
}
}
}
for (int i = 0; i < genome1.GetConnectionGenes().Count; i++)
{
child.AddConnectionGene(newConnectionGenes[i]);
}
//Debug.Log("child "+child);
return(child);
}
private void Awake()
{
if (Manager.gameType == Manager.GameType.Train)
{
// add initial sensors for board
for (int y = 1; y < 21; y++)
{
for (int x = 1; x < 11; x++)
{
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, (y - 1) * 10 + x));
}
}
// add initial sensors for current tetromino
for (int y = 1; y < 5; y++)
{
for (int x = 1; x < 5; x++)
{
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, (y - 1) * 4 + x + 200));
}
}
// add initial sensor for next tetromino
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 217));
// add tetromino position sensor
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 218));
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 219));
// add initial sensor for previous frame DAS
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 220));
// add initial BIAS SENSOR - SHOULD ALWAYS BE SET TO 1
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 221));
//add initial out nodes
// 222 - null
// 223 - left
// 224 - down
// 225 - right
// 226 - a
// 227 - b
for (int i = 222; i < 228; i++)
{
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, i));
}
startingGenome.AddConnectionGene(new ConnectionGene(221, 223, 2f, true, History.Innovate()));
startingGenome.AddConnectionMutation();
startingGenome.AddNodeMutation();
for (int y = 0; y < 20; y++)
{
startingGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 228 + y));
startingGenome.AddConnectionGene(new ConnectionGene(228 + y, Random.Range(222, 228), Random.Range(-2f, 2f), true, History.Innovate()));
}
for (int y = 0; y < 20; y++)
{
for (int x = 0; x < 10; x++)
{
startingGenome.AddConnectionGene(new ConnectionGene(y * 10 + x + 1, 228 + y, Random.Range(0.5f, 2f), true, History.Innovate()));
}
}
}
}
public void SetUp()
{
populationManager = new PopulationManager
{
Callback = this
};
//-----------------------------------------------------------------------------------
// Parent 1
//-----------------------------------------------------------------------------------
parent1Genome = new Genome();
//Create the input nodes
parent1Genome.AddNodeGene(new NodeGene(1, NodeGeneType.INPUT, 0f));
parent1Genome.AddNodeGene(new NodeGene(2, NodeGeneType.INPUT, 0f));
parent1Genome.AddNodeGene(new NodeGene(3, NodeGeneType.INPUT, 0f));
//Create the output node
parent1Genome.AddNodeGene(new NodeGene(4, NodeGeneType.OUTPUT, 1f));
//Create hidden node
parent1Genome.AddNodeGene(new NodeGene(5, NodeGeneType.HIDDEN, 0.5f));
//Create connections
parent1Genome.AddConnectionGene(new ConnectionGene(1, 4, 1.0, true, 1));
parent1Genome.AddConnectionGene(new ConnectionGene(2, 4, 1.0, false, 2));
parent1Genome.AddConnectionGene(new ConnectionGene(3, 4, 1.0, true, 3));
parent1Genome.AddConnectionGene(new ConnectionGene(2, 5, 1.0, true, 4));
parent1Genome.AddConnectionGene(new ConnectionGene(5, 4, 1.0, true, 5));
parent1Genome.AddConnectionGene(new ConnectionGene(1, 5, 1.0, true, 8));
//-----------------------------------------------------------------------------------
// Parent 2
//-----------------------------------------------------------------------------------
parent2Genome = new Genome();
//Create the input nodes
parent2Genome.AddNodeGene(new NodeGene(1, NodeGeneType.INPUT, 0f));
parent2Genome.AddNodeGene(new NodeGene(2, NodeGeneType.INPUT, 0f));
parent2Genome.AddNodeGene(new NodeGene(3, NodeGeneType.INPUT, 0f));
//Create the output node
parent2Genome.AddNodeGene(new NodeGene(4, NodeGeneType.OUTPUT, 1f));
//Create hidden node
parent2Genome.AddNodeGene(new NodeGene(5, NodeGeneType.HIDDEN, 0.4f));
parent2Genome.AddNodeGene(new NodeGene(6, NodeGeneType.HIDDEN, 0.5f));
//Create connections
parent2Genome.AddConnectionGene(new ConnectionGene(1, 4, 1.0, true, 1));
parent2Genome.AddConnectionGene(new ConnectionGene(2, 4, 1.0, false, 2));
parent2Genome.AddConnectionGene(new ConnectionGene(3, 4, 1.0, true, 3));
parent2Genome.AddConnectionGene(new ConnectionGene(2, 5, 1.0, true, 4));
parent2Genome.AddConnectionGene(new ConnectionGene(5, 4, 1.0, false, 5));
parent2Genome.AddConnectionGene(new ConnectionGene(5, 6, 1.0, true, 6));
parent2Genome.AddConnectionGene(new ConnectionGene(6, 4, 1.0, true, 7));
parent2Genome.AddConnectionGene(new ConnectionGene(3, 5, 1.0, true, 9));
parent2Genome.AddConnectionGene(new ConnectionGene(1, 6, 1.0, true, 10));
//-----------------------------------------------------------------------------------
// Parent 3
//-----------------------------------------------------------------------------------
parent3GenomeSimple = new Genome();
//Create the input nodes
parent3GenomeSimple.AddNodeGene(new NodeGene(7, NodeGeneType.INPUT, 0f));
parent3GenomeSimple.AddNodeGene(new NodeGene(8, NodeGeneType.INPUT, 0f));
parent3GenomeSimple.AddNodeGene(new NodeGene(9, NodeGeneType.INPUT, 0f));
//Create the output node
parent3GenomeSimple.AddNodeGene(new NodeGene(10, NodeGeneType.OUTPUT, 1f));
//Create connections
parent3GenomeSimple.AddConnectionGene(new ConnectionGene(7, 10, 1.0, true, 11));
parent3GenomeSimple.AddConnectionGene(new ConnectionGene(8, 10, 1.0, true, 12));
parent3GenomeSimple.AddConnectionGene(new ConnectionGene(9, 10, 1.0, true, 13));
//Init the connection gene counter with 11
connectionInnovationCounter = new GeneCounter(14);
nodeInnovationCounter = new GeneCounter(11);
//Set result values from callback to null
resultAgentsInitalizedAgentList = null;
resultAgentsInitializedSpeciesList = null;
resultAgentKilled = null;
resultAllAgentsKilled = false;
//Set fine tuning parameters
PopulationManager._FACTOR_EXCESS_GENES = 1;
PopulationManager._FACTOR_DISJOINT_GENES = 1;
PopulationManager._FACTOR_AVG_WEIGHT_DIF = 0.4f;
PopulationManager._THRESHOLD_NUMBER_OF_GENES = 20;
PopulationManager._COMPABILITY_THRESHOLD = 3;
}
private void CreateStartingGenomeAndEvaluator()
{
// Create New Genome
Genome genome = new Genome(config.newWeightRange, config.perturbingProbability);
// Check there is at least 1 Input & 1 Output Nodes
if (config.inputNodeNumber == 0)
{
config.inputNodeNumber = 1;
}
if (config.outputNodeNumber == 0)
{
config.outputNodeNumber = 1;
}
// Create Input Nodes
for (int i = 0; i < config.inputNodeNumber; i++)
{
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.INPUT, _nodeInnovation.GetNewInnovationNumber()));
}
// Create Hidden Nodes
foreach (int nb in config.hiddenNodeStartNumberByLayer)
{
for (int i = 0; i < nb; ++i)
{
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, _nodeInnovation.GetNewInnovationNumber()));
}
}
// Create Output Nodes
for (int i = 0; i < config.outputNodeNumber; i++)
{
genome.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, _nodeInnovation.GetNewInnovationNumber()));
}
// Create Connections
if (config.addConnectionOnCreation)
{
if (config.hiddenNodeStartNumberByLayer.Count > 0)
{
int inputStartId = 0;
int previousHiddenStatId = 0;
int previousHiddenStopId = 0;
int hiddenStartId = config.inputNodeNumber;
int hiddenStopId = config.inputNodeNumber;
int outputStartId = genome.Nodes.Count - config.outputNodeNumber;
// Loop through Hidden Layers
for (int hiddenLayer = 0; hiddenLayer < config.hiddenNodeStartNumberByLayer.Count; hiddenLayer++)
{
// Get Hidden Start & Stop Ids
if (hiddenLayer > 0)
{
hiddenStartId += config.hiddenNodeStartNumberByLayer[hiddenLayer - 1];
}
hiddenStopId += config.hiddenNodeStartNumberByLayer[hiddenLayer];
// Loop through Nodes of the current Layer
for (int hiddenNodeId = hiddenStartId; hiddenNodeId < hiddenStopId; ++hiddenNodeId)
{
// If current Hidden Layer is the first Layer
if (hiddenLayer == 0)
{
// Add Connections from Inputs to First Hidden Layer
for (int inputNodeId = inputStartId; inputNodeId < config.inputNodeNumber; ++inputNodeId)
{
genome.AddConnectionGene(new ConnectionGene(inputNodeId, hiddenNodeId, Random.Range(config.newWeightRange.x, config.newWeightRange.y), true, _connectionInnovation.GetNewInnovationNumber()));
}
}
else
{
// Add Connections from previous Hidden Layer to current Hidden Layer
for (int previousHiddenNodeId = previousHiddenStatId; previousHiddenNodeId < previousHiddenStopId; ++previousHiddenNodeId)
{
genome.AddConnectionGene(new ConnectionGene(previousHiddenNodeId, hiddenNodeId, Random.Range(config.newWeightRange.x, config.newWeightRange.y), true, _connectionInnovation.GetNewInnovationNumber()));
}
// If current Hidden Layer is the last Layer
if (hiddenLayer + 1 == config.hiddenNodeStartNumberByLayer.Count)
{
// Add Connections from Last Hidden Layer to Outputs
for (int outputNodeId = outputStartId; outputNodeId < genome.Nodes.Count; ++outputNodeId)
{
genome.AddConnectionGene(new ConnectionGene(hiddenNodeId, outputNodeId, Random.Range(config.newWeightRange.x, config.newWeightRange.y), true, _connectionInnovation.GetNewInnovationNumber()));
}
}
}
}
// Save previous Hidden Layer Start & Stop Ids
previousHiddenStatId = hiddenStartId;
previousHiddenStopId = hiddenStopId;
}
}
else
{
int outputStartId = config.inputNodeNumber;
int outputStopId = config.inputNodeNumber + config.outputNodeNumber;
// Loop Input Node
for (int inputNodeId = 0; inputNodeId < outputStartId; ++inputNodeId)
{
// Loop Output Node & add Connection between Input Node & Hidden Node
for (int outputNodeId = outputStartId; outputNodeId < outputStopId; ++outputNodeId)
{
genome.AddConnectionGene(new ConnectionGene(inputNodeId, outputNodeId, Random.Range(config.newWeightRange.x, config.newWeightRange.y), true, _connectionInnovation.GetNewInnovationNumber()));
}
}
}
}
_startingGenome = genome;
Debug.Log("Starting Genome:\n" + genome.ToString());
// Create Evaluator
_evaluator = new CreatureEvaluator(config, genome, _nodeInnovation, _connectionInnovation);
}
public void SetUp()
{
//-----------------------------------------------------------------------------------
// Parent 1
//-----------------------------------------------------------------------------------
parent1Genome = new Genome();
//Create the input nodes
parent1Genome.AddNodeGene(new NodeGene(1, NodeGeneType.INPUT, 0f));
parent1Genome.AddNodeGene(new NodeGene(2, NodeGeneType.INPUT, 0f));
parent1Genome.AddNodeGene(new NodeGene(3, NodeGeneType.INPUT, 0f));
//Create the output node
parent1Genome.AddNodeGene(new NodeGene(4, NodeGeneType.OUTPUT, 1f));
//Create hidden node
parent1Genome.AddNodeGene(new NodeGene(5, NodeGeneType.HIDDEN, 0.5f));
//Create connections
parent1Genome.AddConnectionGene(new ConnectionGene(1, 4, 1.0, true, 1));
parent1Genome.AddConnectionGene(new ConnectionGene(2, 4, 1.0, false, 2));
parent1Genome.AddConnectionGene(new ConnectionGene(3, 4, 1.0, true, 3));
parent1Genome.AddConnectionGene(new ConnectionGene(2, 5, 1.0, true, 4));
parent1Genome.AddConnectionGene(new ConnectionGene(5, 4, 1.0, true, 5));
parent1Genome.AddConnectionGene(new ConnectionGene(1, 5, 1.0, true, 8));
//-----------------------------------------------------------------------------------
// Parent 2
//-----------------------------------------------------------------------------------
parent2Genome = new Genome();
//Create the input nodes
parent2Genome.AddNodeGene(new NodeGene(1, NodeGeneType.INPUT, 0f));
parent2Genome.AddNodeGene(new NodeGene(2, NodeGeneType.INPUT, 0f));
parent2Genome.AddNodeGene(new NodeGene(3, NodeGeneType.INPUT, 0f));
//Create the output node
parent2Genome.AddNodeGene(new NodeGene(4, NodeGeneType.OUTPUT, 1f));
//Create hidden node
parent2Genome.AddNodeGene(new NodeGene(5, NodeGeneType.HIDDEN, 0.4f));
parent2Genome.AddNodeGene(new NodeGene(6, NodeGeneType.HIDDEN, 0.6f));
//Create connections
parent2Genome.AddConnectionGene(new ConnectionGene(1, 4, 1.0, true, 1));
parent2Genome.AddConnectionGene(new ConnectionGene(2, 4, 1.0, false, 2));
parent2Genome.AddConnectionGene(new ConnectionGene(3, 4, 1.0, true, 3));
parent2Genome.AddConnectionGene(new ConnectionGene(2, 5, 1.0, true, 4));
parent2Genome.AddConnectionGene(new ConnectionGene(5, 4, 1.0, false, 5));
parent2Genome.AddConnectionGene(new ConnectionGene(5, 6, 1.0, true, 6));
parent2Genome.AddConnectionGene(new ConnectionGene(6, 4, 1.0, true, 7));
parent2Genome.AddConnectionGene(new ConnectionGene(3, 5, 1.0, true, 9));
parent2Genome.AddConnectionGene(new ConnectionGene(1, 6, 1.0, true, 10));
//-----------------------------------------------------------------------------------
// Feed forward network
//-----------------------------------------------------------------------------------
//Nodes
feedForwardNetwork = new Genome();
feedForwardNetwork.AddNodeGene(new NodeGene(0, NodeGeneType.INPUT, 0f));
feedForwardNetwork.AddNodeGene(new NodeGene(1, NodeGeneType.INPUT, 0f));
feedForwardNetwork.AddNodeGene(new NodeGene(2, NodeGeneType.OUTPUT, 1f));
feedForwardNetwork.AddNodeGene(new NodeGene(3, NodeGeneType.OUTPUT, 1f));
feedForwardNetwork.AddNodeGene(new NodeGene(4, NodeGeneType.HIDDEN, 0.5f));
feedForwardNetwork.AddNodeGene(new NodeGene(5, NodeGeneType.HIDDEN, 0.5f));
feedForwardNetwork.AddNodeGene(new NodeGene(6, NodeGeneType.HIDDEN, 0.5f));
//Connections
feedForwardNetwork.AddConnectionGene(new ConnectionGene(0, 4, 0.2, true, 0));
feedForwardNetwork.AddConnectionGene(new ConnectionGene(0, 5, 0.3, true, 1));
feedForwardNetwork.AddConnectionGene(new ConnectionGene(1, 5, 0.4, true, 2));
feedForwardNetwork.AddConnectionGene(new ConnectionGene(1, 6, 0.5, true, 3));
feedForwardNetwork.AddConnectionGene(new ConnectionGene(4, 2, 0.6, true, 4));
feedForwardNetwork.AddConnectionGene(new ConnectionGene(5, 2, 0.7, true, 5));
feedForwardNetwork.AddConnectionGene(new ConnectionGene(5, 3, 0.8, true, 6));
feedForwardNetwork.AddConnectionGene(new ConnectionGene(6, 3, 0.9, true, 7));
//-----------------------------------------------------------------------------------
// Recurrent network
//-----------------------------------------------------------------------------------
recurrentNetwork = new Genome(feedForwardNetwork);
recurrentNetwork.AddConnectionGene(new ConnectionGene(2, 4, -2, true, 8));
recurrentNetwork.AddConnectionGene(new ConnectionGene(6, 6, -2, true, 9));
}
void Start()
{
History.nodeInnovation = 0;
// FIRST PARENT
firstParent.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 1));
firstParent.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 2));
firstParent.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 3));
firstParent.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, 4));
firstParent.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 5));
// CONNECTIONS
firstParent.AddConnectionGene(new ConnectionGene(1, 4, 1f, true, 1));
firstParent.AddConnectionGene(new ConnectionGene(2, 4, 1f, false, 2));
firstParent.AddConnectionGene(new ConnectionGene(3, 4, 1f, true, 3));
firstParent.AddConnectionGene(new ConnectionGene(2, 5, 1f, true, 4));
firstParent.AddConnectionGene(new ConnectionGene(5, 4, 1f, true, 5));
firstParent.AddConnectionGene(new ConnectionGene(1, 5, 1f, true, 8));
// SECOND PARENT
secondParent.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 1));
secondParent.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 2));
secondParent.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, 3));
secondParent.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, 4));
secondParent.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 5));
secondParent.AddNodeGene(new NodeGene(NodeGene.TYPE.HIDDEN, 6));
// CONNECTIONS
secondParent.AddConnectionGene(new ConnectionGene(1, 4, 1f, true, 1));
secondParent.AddConnectionGene(new ConnectionGene(2, 4, 1f, false, 2));
secondParent.AddConnectionGene(new ConnectionGene(3, 4, 1f, true, 3));
secondParent.AddConnectionGene(new ConnectionGene(2, 5, 1f, true, 4));
secondParent.AddConnectionGene(new ConnectionGene(5, 4, 1f, false, 5));
secondParent.AddConnectionGene(new ConnectionGene(5, 6, -1f, true, 6));
secondParent.AddConnectionGene(new ConnectionGene(6, 4, 1f, true, 7));
secondParent.AddConnectionGene(new ConnectionGene(3, 5, 1f, true, 9));
secondParent.AddConnectionGene(new ConnectionGene(1, 6, 1f, true, 10));
// SIMPLE GENOME
simpleGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, History.NodeInnovate()));
simpleGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, History.NodeInnovate()));
simpleGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.SENSOR, History.NodeInnovate()));
simpleGenome.AddNodeGene(new NodeGene(NodeGene.TYPE.OUTPUT, History.NodeInnovate()));
simpleGenome.AddConnectionGene(new ConnectionGene(1, 4, -1f, true, History.Innovate()));
simpleGenome.AddConnectionGene(new ConnectionGene(2, 4, 1f, true, History.Innovate()));
simpleGenome.AddConnectionGene(new ConnectionGene(3, 4, 1f, true, History.Innovate()));
//simpleGenome.AddConnectionGene(new ConnectionGene(2, 3, 1f, true, History.Innovate()));
Genome offspringGenome = Genome.Crossover(secondParent, firstParent);
int numToRender = 1003;
int scale = 20;
NEATRenderer renderer = new NEATRenderer();
for (int i = 0; i < numToRender; i += 100)
{
renderer.DrawGenome(TetrisNEAT.OpenGenome("/" + i + ".tetro"), new Vector3((scale + 1) * (i + 1), 0, 0), Vector2.one * scale);
}
// Un-comment the below line to conduct a test with the current evaluator after first removing the rendering instructions
//StartCoroutine(SimpleTest());
}
public void LoadGenome(string filename, bool all)
{
string path = filename;
Genome genome = new Genome();
using (StreamReader reader = new StreamReader(path))
{
bool node = false;
bool connection = false;
string line;
while ((line = reader.ReadLine()) != null)
{
if (line.Equals("Nodes"))
{
node = true;
connection = false;
}
else if (line.Equals("Connections"))
{
node = false;
connection = true;
}
else
{
string[] info = line.Split(',');
if (node)
{
int id = int.Parse(info[0]);
NodeGene.Type type = (NodeGene.Type)System.Enum.Parse(typeof(NodeGene.Type), info[1]);
GenomeUtils.Activation activation = (GenomeUtils.Activation)System.Enum.Parse(typeof(GenomeUtils.Activation), info[2]);
genome.AddNodeGene(new NodeGene(type, id, activation));
Counter.SetNodeCounter(id);
}
else if (connection)
{
int innovation = int.Parse(info[0]);
bool expressed = bool.Parse(info[1]);
int inNode = int.Parse(info[2]);
int outNode = int.Parse(info[3]);
float weight = float.Parse(info[4]);
genome.AddConnectionGene(new ConnectionGene(inNode, outNode, weight, expressed, innovation));
Counter.SetConnectionCounter(innovation);
}
else
{
Debug.LogError("Invalid genome file");
}
}
}
}
genomes.Clear();
genomes.Add(genome);
if (all)
{
for (int i = 1; i < GenomeUtils.POP_SIZE; i++)
{
genomes.Add(GenomeUtils.Clone(genome));
}
}
else
{
for (int i = 1; i < GenomeUtils.POP_SIZE; i++)
{
genomes.Add(new Genome(inputNodes, outputNodes));
}
}
SetSpecies();
MakeNNets();
}