public void AddConnectionMutation(Random r)
{
int listSize = Nodes.Count;
NodeGene node1 = Nodes[Random.Range(0, listSize)];
NodeGene node2 = Nodes[Random.Range(0, listSize)];
bool reversed = false;
if (node1.GetType().Equals(NodeGene.NodeType.HIDDEN) && node2.GetType().Equals(NodeGene.NodeType.INPUT))
{
reversed = true;
}
else if (node1.GetType().Equals(NodeGene.NodeType.OUTPUT) && node2.GetType().Equals(NodeGene.NodeType.HIDDEN))
{
reversed = true;
}
else if (node1.GetType().Equals(NodeGene.NodeType.OUTPUT) && node2.GetType().Equals(NodeGene.NodeType.INPUT))
{
reversed = true;
}
bool connectionExists = false;
foreach (ConnectionGene con in Connections.Values)
{
if (con.InNode == node1.ID && con.OutNode == node2.ID)
{
connectionExists = true;
break;
}
else if (con.InNode == node2.ID && con.OutNode == node1.ID)
{
connectionExists = true;
break;
}
}
if (connectionExists)
{
return;
}
ConnectionGene newCon = new ConnectionGene(reversed ? node2.ID : node1.ID, reversed ? node1.ID : node2.ID, Random.Range(0f, 1f), true, 0);
Connections.Add(newCon.Innovation, newCon);
}
public void AddNodeMutation(Counter innovation)
{
int listSize = Connections.Count;
ConnectionGene con = Connections[Random.Range(0, listSize)];
NodeGene inNode = Nodes[con.InNode];
NodeGene outNode = Nodes[con.OutNode];
con.Expressed = false;
NodeGene newNode = new NodeGene(NodeGene.NodeType.HIDDEN, Nodes.Count);
ConnectionGene inToNew = new ConnectionGene(inNode.ID, newNode.ID, 1f, true, innovation.GetInnovation());
ConnectionGene newToOut = new ConnectionGene(newNode.ID, outNode.ID, con.Weight, true, innovation.GetInnovation());
Nodes.Add(newNode.ID, newNode);
Connections.Add(inToNew.Innovation, inToNew);
Connections.Add(newToOut.Innovation, newToOut);
}
/**
* @param parent1 More fit parent
* @param parent2 Less fit parent
* Operating on a Genome object
*/
public void Crossover(Genome parent1, Genome parent2)
{
// Genome child = new Genome();
foreach (NodeGene parentNode in parent1.Nodes.Values)
{
AddNodeGene(parentNode.Copy());
}
foreach (ConnectionGene parentNode in parent1.Connections.Values)
{
if (parent2.Connections.ContainsValue(parentNode)) // matching gene
{
ConnectionGene childConGene = (Random.Range(0f, 1f) >= 0.5) ? parentNode.Copy() : parent2.Connections[parentNode.Innovation].Copy();
AddConnectionGene(childConGene);
}
else // disjoint or excess gene
{
ConnectionGene childConGene = parentNode.Copy();
AddConnectionGene(childConGene);
}
}
//return child;
}
private Neuron.ActivationType _activationType; // ActivationType
public NeuralNetwork(Genome genome, Neuron.ActivationType activationType = Neuron.ActivationType.SIGMOID, bool bias = true, int timeOut = 1000)
{
_activationType = activationType;
_bias = bias;
_timeOut = timeOut;
_inputIds = new List <int>();
_outputIds = new List <int>();
_neurons = new Dictionary <int, Neuron>();
_unprocessedNeurons = new List <Neuron>();
Genome = genome;
Fitness = 0f;
// Fill Neurons, Input & Outputs Ids w/ Nodes in Genome
foreach (int nodeId in genome.Nodes.Keys)
{
NodeGene node = genome.Nodes[nodeId];
Neuron neuron = null;
// Input & Output Node
if (node.Type == NodeGene.TYPE.INPUT)
{
neuron = new Neuron(Neuron.NeuronType.INPUT, _activationType, false); // No bias on Input Node
neuron.AddInputConnection();
_inputIds.Add(nodeId);
}
else if (node.Type == NodeGene.TYPE.OUTPUT)
{
neuron = new Neuron(Neuron.NeuronType.OUTPUT, _activationType, _bias);
_outputIds.Add(nodeId);
}
else
{
neuron = new Neuron(Neuron.NeuronType.HIDDEN, _activationType, _bias);
}
// Add Neuron to the Network
_neurons.Add(nodeId, neuron);
}
_inputIds.Sort();
_outputIds.Sort();
// Add Genome Connections to Neurons
foreach (int connectionId in genome.Connections.Keys)
{
ConnectionGene connection = genome.Connections[connectionId];
// Ignore Disabled Nodes
if (!connection.IsEnable)
{
continue;
}
// Add Output Connection to the Neuron of the emitting Node
Neuron emittingNeuron = _neurons[connection.InNode];
emittingNeuron.AddOutputConnection(connection.OutNode, connection.Weight);
// Add Input Connection to the Neuron of the receiving Node
Neuron receivingNeuron = _neurons[connection.OutNode];
receivingNeuron.AddInputConnection();
}
}
public void AddConnectionGene(ConnectionGene gene)
{
Connections.Add(gene.Innovation, gene);
}
public static float CompatibilityDistance(Genome genome1, Genome genome2, float c1, float c2, float c3)
{
int matchingGenes = 0;
int disjointGenes = 0;
int excessGenes = 0;
float weightDifference = 0;
float avgWeightDiff = 0;
float compatibilityDistance = 0;
int highestNodeInnovation1 = genome1.Nodes.Keys.Max(); // find largest innovation number
int highestNodeInnovation2 = genome2.Nodes.Keys.Max();
int indicesNode = Mathf.Max(highestNodeInnovation1, highestNodeInnovation2);
for (int i = 0; i <= indicesNode; i++)
{ // loop through genes -> i is innovation numbers
NodeGene node1 = genome1.Nodes[i];
NodeGene node2 = genome2.Nodes[i];
if (node1 != null && node2 != null)
{
// both genomes has the gene w/ this innovation number
matchingGenes++;
}
else if (node1 == null && node2 != null && highestNodeInnovation1 > i)
{
// genome 1 lacks gene, genome 2 has gene, genome 1 has more genes w/ higher innovation numbers
disjointGenes++;
}
else if (node1 != null && node2 == null && highestNodeInnovation2 > i)
{
// genome 2 lacks gene, genome 1 has gene, genome 2 has more genes w/ higher innovation numbers
disjointGenes++;
}
else if (node1 == null && node2 != null && highestNodeInnovation1 < i)
{
// genome 1 lacks gene, genome 2 has gene, genome 2 has more genes w/ higher innovation numbers
excessGenes++;
}
else if (node1 != null && node2 == null && highestNodeInnovation2 < i)
{
// genome 2 lacks gene, genome 1 has gene, genome 1 has more genes w/ higher innovation numbers
excessGenes++;
}
}
int highestConnectionInnovation1 = genome1.Connections.Keys.Max(); // find largest innovation number
int highestConnectionInnovation2 = genome2.Connections.Keys.Max();
int indicesCon = Mathf.Max(highestConnectionInnovation1, highestConnectionInnovation2);
for (int i = 0; i <= indicesCon; i++)
{ // loop through genes -> i is innovation numbers
ConnectionGene connection1 = genome1.Connections[i];
ConnectionGene connection2 = genome2.Connections[i];
if (connection1 != null && connection2 != null)
{
// both genomes has the gene w/ this innovation number
matchingGenes++;
weightDifference += Mathf.Abs(connection1.Weight - connection2.Weight);
}
else if (connection1 == null && connection2 != null && highestConnectionInnovation1 > i)
{
// genome 1 lacks gene, genome 2 has gene, genome 1 has more genes w/ higher innovation numbers
disjointGenes++;
}
else if (connection1 != null && connection2 == null && highestConnectionInnovation2 > i)
{
// genome 2 lacks gene, genome 1 has gene, genome 2 has more genes w/ higher innovation numbers
disjointGenes++;
}
else if (connection1 == null && connection2 != null && highestConnectionInnovation1 < i)
{
// genome 1 lacks gene, genome 2 has gene, genome 1 has more genes w/ higher innovation numbers
excessGenes++;
}
else if (connection1 != null && connection2 == null && highestConnectionInnovation2 < i)
{
// genome 2 lacks gene, genome 1 has gene, genome 2 has more genes w/ higher innovation numbers
excessGenes++;
}
}
avgWeightDiff = weightDifference / matchingGenes;
float N = 1; // number of genes in largest parent, 1 if less than 20 genes
compatibilityDistance = excessGenes * c1 / N + disjointGenes * c2 / N + avgWeightDiff * c3;
return(compatibilityDistance);
}
/// <summary>
/// Add Connection Gene
/// </summary>
/// <param name="connection">Connection</param>
public void AddConnectionGene(ConnectionGene connection)
{
Connections[connection.InnovationId] = connection;
}
/// <summary>
/// Add a new Connection between 2 Random Nodes
/// </summary>
/// <param name="r">Random</param>
/// <param name="connectionInnovationCounter">Connection Innovation Counter</param>
/// <param name="maxTries">Max Tries to attemp Mutation</param>
/// <returns>Success</returns>
public bool AddConnectionMutation(Random r, InnovationCounter connectionInnovationCounter, int maxTries = 10)
{
bool success = false;
// Try maxTries times
for (int tries = 0; tries < maxTries && !success; tries++)
{
// Get 2 Random Nodes & a Random Weight
List <int> nodeInnovationIds = new List <int>(Nodes.Keys);
NodeGene node1 = Nodes[nodeInnovationIds[r.Next(nodeInnovationIds.Count)]];
NodeGene node2 = Nodes[nodeInnovationIds[r.Next(nodeInnovationIds.Count)]];
// Sigmoid Weights
// float weight = (float)r.NextDouble() * 2f - 1f;
// Tanh Weights
// float weight = UnityEngine.Random.Range(-0.5f, 0.5f);
// Config Weights
float weight = UnityEngine.Random.Range(NewWeightRange.x, NewWeightRange.y);
// Is Reversed ?
if ((node1.Type == NodeGene.TYPE.HIDDEN && node2.Type == NodeGene.TYPE.INPUT) ||
(node1.Type == NodeGene.TYPE.OUTPUT && node2.Type == NodeGene.TYPE.HIDDEN) ||
(node1.Type == NodeGene.TYPE.OUTPUT && node2.Type == NodeGene.TYPE.INPUT))
{
NodeGene swap = node1;
node1 = node2;
node2 = swap;
}
// Is Connection Impossible ?
if ((node1.Type == NodeGene.TYPE.INPUT && node2.Type == NodeGene.TYPE.INPUT) ||
(node1.Type == NodeGene.TYPE.OUTPUT && node2.Type == NodeGene.TYPE.OUTPUT) ||
(node1 == node2))
{
continue;
}
// Does Connection already exists ?
bool connectionExists = false;
foreach (ConnectionGene c in Connections.Values)
{
if ((c.InNode == node1.Id && c.OutNode == node2.Id) ||
(c.InNode == node2.Id && c.OutNode == node1.Id))
{
connectionExists = true;
break;
}
}
if (connectionExists)
{
continue;
}
// Circular structure ?
bool connectionImpossible = false;
List <int> nodeIds = new List <int>(); // Node that need output from node2
List <int> nodeToCheck = new List <int>(); // Nodes to check
foreach (int connectionId in Connections.Keys) // Get all Connections w/ outNode == node2
{
ConnectionGene connection = Connections[connectionId];
if (connection.InNode == node2.Id) // Connection comes from node2
{
nodeIds.Add(connection.OutNode);
nodeToCheck.Add(connection.OutNode);
}
}
while (nodeToCheck.Count > 0) // Get all Connections w/ outNode == nodeToCheck
{
int nodeId = nodeToCheck[0];
foreach (int connectionId in Connections.Keys)
{
ConnectionGene connection = Connections[connectionId];
if (connection.InNode == nodeId) // Connection comes from nodeToCheck
{
nodeIds.Add(connection.OutNode);
nodeToCheck.Add(connection.OutNode);
}
}
nodeToCheck.RemoveAt(0);
}
foreach (int i in nodeIds) // Loop through all Node Ids
{
if (i == node1.Id) // If one of the Node == node1 => Connection is Impossible
{
connectionImpossible = true;
break;
}
}
if (connectionImpossible)
{
continue;
}
// Add new Connection
ConnectionGene newConnection = new ConnectionGene(
node1.Id,
node2.Id,
weight,
true,
connectionInnovationCounter.GetNewInnovationNumber()
);
Connections.Add(newConnection.InnovationId, newConnection);
success = true;
}
return(success);
}