/// <summary>
/// Adds a node by selecting a random connection, disabling it and replacing it by 2 genes.
/// The first gene goes from the original input node, to the new node with a weight of 1.
/// The second gene goes from the the new node to the old output node with the same weight as the original connection.
/// </summary>
/// <param name="trainingRoomSettings">The training room settings.</param>
/// <param name="getAndIncreaseNodeIdFunction">The get and increase node id function.</param>
/// <param name="innovationFunction">The innovation function.</param>
private void AddNodeMutation(TrainingRoomSettings trainingRoomSettings, Func <uint> getAndIncreaseNodeIdFunction, Func <uint, uint, uint> innovationFunction)
{
// If the connection genes count is 0, then there are not connection genes to mutate.
if (ConnectionGenes.Count == 0)
{
return;
}
// Find a random connection.
ConnectionGene theChosenOne = ConnectionGenes.ElementAt(trainingRoomSettings.Random.Next(ConnectionGenes.Count));
// Disable the connection gene.
theChosenOne.Enabled = false;
// Generate the new node's id.
uint newNodeId = getAndIncreaseNodeIdFunction();
// Get the old in and out node identifiers.
uint oldInId = theChosenOne.InNodeIdentifier;
uint oldOutId = theChosenOne.OutNodeIdentifier;
// Create a connectionGene from oldIn (a) to new (c) and from new (c) to oldOut (b)
ConnectionGene aToC = new ConnectionGene(Id, innovationFunction(oldInId, newNodeId), oldInId, newNodeId, 1);
ConnectionGene cToB = new ConnectionGene(Id, innovationFunction(newNodeId, oldOutId), newNodeId, oldOutId, theChosenOne.Weight);
// Add new connection genes.
ConnectionGenes.Add(aToC);
ConnectionGenes.Add(cToB);
// Update the max innovation.
_maxInnovation = Math.Max(Math.Max(cToB.InnovationNumber, aToC.InnovationNumber), _maxInnovation);
}
/// <summary>
/// Adds a node by selecting a random connection, disabling it and replacing it by 2 genes.
/// The first gene goes from the original input node, to the new node with a weight of 1.
/// The second gene goes from the the new node to the old output node with the same weight as the original connection.
/// </summary>
private void AddNodeMutation()
{
if (ConnectionGenes.Count == 0)
{
return;
}
// Choose a random connection to add a node into
ConnectionGene theChosenOne = ConnectionGenes.ElementAt(TrainingRoom.Random.Next(ConnectionGenes.Count));
// Disable it
theChosenOne.Enabled = false;
// Generate the new node's id
uint newNodeId = TrainingRoom.GetAndIncreaseNodeId();
uint oldInId = theChosenOne.InId;
uint oldOutId = theChosenOne.OutId;
// Create a connectionGene from oldIn (a) to new (c) and from new (c) to oldOut (b)
ConnectionGene aToC = new ConnectionGene(Id, oldInId, newNodeId, 1, TrainingRoom.GetInnovationNumber(oldInId, newNodeId));
ConnectionGene cToB = new ConnectionGene(Id, newNodeId, oldOutId, theChosenOne.Weight, TrainingRoom.GetInnovationNumber(newNodeId, oldOutId));
ConnectionGenes.Add(aToC);
ConnectionGenes.Add(cToB);
_maxInnovation = Math.Max(Math.Max(cToB.InnovationNumber, aToC.InnovationNumber), _maxInnovation);
}
/// <summary>
/// Mutates the the organism based on the training room settings.
/// </summary>
/// <param name="trainingRoomSettings">The training room settings.</param>
/// <param name="getAndIncreaseNodeIdFunction">The get and increase node id function.</param>
/// <param name="innovationFunction">The innovation function.</param>
public void Mutate(TrainingRoomSettings trainingRoomSettings, Func <uint> getAndIncreaseNodeIdFunction, Func <uint, uint, uint> innovationFunction)
{
// If the random value is lower than the add connection chance add a connection mutation.
if (trainingRoomSettings.Random.NextDouble() < trainingRoomSettings.AddConnectionChance)
{
AddConnectionMutation(trainingRoomSettings, innovationFunction);
}
// If the random value is lower than the add node chance add a node mutation.
if (trainingRoomSettings.Random.NextDouble() < trainingRoomSettings.AddNodeChance)
{
AddNodeMutation(trainingRoomSettings, getAndIncreaseNodeIdFunction, innovationFunction);
}
// If the random value is higher than the mutate weight chance or the connection gene count is lower than 0 return early.
if (trainingRoomSettings.Random.NextDouble() > trainingRoomSettings.MutateWeightChance || ConnectionGenes.Count <= 0)
{
return;
}
// Find a random connection gene.
ConnectionGene connectionGene = ConnectionGenes.ElementAt(trainingRoomSettings.Random.Next(ConnectionGenes.Count));
// If the random value is lower than the weight reassign chance set a new weight else add weight.
if (trainingRoomSettings.Random.NextDouble() < trainingRoomSettings.WeightReassignChance)
{
connectionGene.Weight = trainingRoomSettings.Random.NextDouble() * 2 - 1;
}
else
{
connectionGene.Weight += (trainingRoomSettings.Random.NextDouble() * 2 - 1) * 0.1;
}
//TODO: Inputs mutate?
}
/// <summary>
/// Mutates the brain, each time this is called there is a chance to:
/// - Add a connection
/// - Add a node
/// - Change the weight of an existing gene, which can either randomly be reset to a random value or slightly change
/// These changes can all happen in one call, but the chance that this happens depends on the training room settings.
/// </summary>
public void Mutate()
{
if (TrainingRoom.Random.NextDouble() < TrainingRoom.TrainingRoomSettings.AddConnectionChance)
{
AddConnectionMutation();
}
if (TrainingRoom.Random.NextDouble() < TrainingRoom.TrainingRoomSettings.AddNodeChance)
{
AddNodeMutation();
}
if ((TrainingRoom.Random.NextDouble() < TrainingRoom.TrainingRoomSettings.MutateWeightChance) && ConnectionGenes.Count > 0)
{
ConnectionGene connectionGene = ConnectionGenes.ElementAt(TrainingRoom.Random.Next(ConnectionGenes.Count));
if (TrainingRoom.Random.NextDouble() < TrainingRoom.TrainingRoomSettings.WeightReassignChance)
{
connectionGene.Weight = TrainingRoom.Random.NextDouble() * 2 - 1;
}
else
{
connectionGene.Weight += (TrainingRoom.Random.NextDouble() * 2 - 1) * 0.1;
}
}
}