/// <summary>
/// Retrieves the id of a matching innovation.
/// </summary>
/// <param name="innovInfo">The information to search for.</param>
/// <returns>The id of the first matching innovation. (-1) if not found.</returns>
public int FindByInnovation(InnovationInformation innovInfo)
{
for (int i = 0; i < Size(); i++)
{
if (innovInfo.IsSameAs(Pool[i]))
{
return(i);
}
}
return(-1);
}
/// <summary>
/// Mutates a genome by breaking a connection up into two separate connections.
/// </summary>
/// <param name="genome">The genome to be modified.</param>
/// <param name="innovationsSeen">A list of previously seen innovations.</param>
/// <param name="rando">A random number generator.</param>
public static void MutateAddNode(Genome genome, InnovationPool innovationsSeen, Random rando)
{
List <Gene> possibleConnections = new List <Gene>(genome.Genes);
possibleConnections.RemoveAll(x => x.Frozen || NodePool.FindById(x.link.InNode).Type == NodeType.BIAS);
if (possibleConnections.Count == 0)
{
return;
}
//TODO: Note in original algorithm saying uniform distribution is not optimal here.
Gene geneToSplit = possibleConnections[rando.Next(possibleConnections.Count)];
geneToSplit.Frozen = true;
ActivationStyle style = ActivationFunctions.ChooseActivationStyle(rando);
InnovationInformation innovation = new InnovationInformation(geneToSplit.link, style);
int firstConId = -1;
int secondConId = -1;
int registeredInnovationId = innovationsSeen.FindByInnovation(innovation);
if (registeredInnovationId == -1)
{
int newNodeId = NodePool.Add(new NodeInformation(NodeType.HIDDEN, style));
ConnectionInformation firstConnect = new ConnectionInformation(geneToSplit.link.InNode, newNodeId);
firstConId = ConnectionPool.Add(firstConnect);
ConnectionInformation secondConnect = new ConnectionInformation(newNodeId, geneToSplit.link.OutNode);
secondConId = ConnectionPool.Add(secondConnect);
innovation.NewNodeDetails.NewNodeId = newNodeId;
innovation.NewNodeDetails.FirstConnectionId = firstConId;
innovation.NewNodeDetails.SecondConnectionId = secondConId;
innovationsSeen.Add(innovation);
}
else
{
InnovationInformation registeredInnovation = innovationsSeen.FindById(registeredInnovationId);
firstConId = registeredInnovation.NewNodeDetails.FirstConnectionId;
secondConId = registeredInnovation.NewNodeDetails.SecondConnectionId;
}
genome.Genes.Add(new Gene(ConnectionPool.FindById(firstConId), firstConId, 1.0, false));
genome.Genes.Add(new Gene(ConnectionPool.FindById(secondConId), secondConId, geneToSplit.Weight, false));
}
/// <summary>
/// Checks if the two innovations are equivalent.
/// </summary>
/// <param name="other">The innovation to compare against.</param>
/// <returns>True if they are the same.</returns>
public bool IsSameAs(InnovationInformation other)
{
if (InnovationType == MutationStyle.AddConnection)
{
return(InnovationType == other.InnovationType &&
ConnectionInformation.IsSameAs(other.ConnectionInformation));
}
else if (InnovationType == MutationStyle.AddNode)
{
return(InnovationType == other.InnovationType &&
ConnectionInformation.IsSameAs(other.ConnectionInformation) &&
Style == other.Style);
}
return(false);
}
/// <summary>
/// Creates an initial population.
/// </summary>
/// <param name="nodes">A list of NodeType-ActivationStyle pairing. The node Id will be the position in the list.</param>
/// <param name="connections">A list of InNodeId-OutNodeId-Weight tuples.</param>
/// <param name="populationSize">The size of the population to test.</param>
/// <param name="rando">A random number generator for perturbing the weights.</param>
public Population(List <Tuple <NodeType, ActivationStyle> > nodes, List <Tuple <int, int, double> > connections, int populationSize, Random rando)
{
TargetPopulationSize = populationSize;
ValidateConstructorParameters(nodes.Count, connections);
for (int i = 0; i < nodes.Count; i++)
{
NodePool.Add(new NodeInformation(nodes[i].Item1, nodes[i].Item2));
}
List <Gene> startGenes = new List <Gene>();
foreach (var tupe in connections)
{
ConnectionInformation ci = new ConnectionInformation(tupe.Item1, tupe.Item2);
startGenes.Add(new Gene(ci, ConnectionPool.Size(), tupe.Item3, false));
InnovationInformation info = new InnovationInformation(ci);
info.NewConnectionDetails.ConnectionId = ConnectionPool.Size();
GenerationalInnovations.Add(info);
ConnectionPool.Add(ci);
}
Genome adam = new Genome(startGenes);
List <Genome> firstGen = new List <Genome>()
{
adam
};
for (int i = 1; i < TargetPopulationSize; i++)
{
Genome copy = new Genome(adam);
Mutation.MutateTryAllNonStructural(copy, rando);
firstGen.Add(copy);
}
SpeciateNewGeneration(firstGen);
}
/// <summary>
/// Mutates a given genome by adding a connection.
/// Connection is guaranteed to not be 'into' a sensor or bias.
/// </summary>
/// <param name="genome">The genome to be modified.</param>
/// <param name="innovationsSeen">A list of previously seen innovations.</param>
/// <param name="rando">A random number generator.</param>
public static void MutateAddConnection(Genome genome, InnovationPool innovationsSeen, Random rando)
{
//TODO: I'm getting the node information, but I only need that to construct allNodesNotInput...
Dictionary <int, NodeInformation> allNodes = genome.GetAllNodeInformation(true);
Dictionary <int, NodeInformation> allNodesNotInput = new Dictionary <int, NodeInformation>(allNodes);
//TODO: Witnessed a bug where allNodes.Count == 0.
// Could be a node where there are only frozen links connecting.
foreach (var id in allNodesNotInput.Where(kvp => kvp.Value.IsInput()).ToList())
{
allNodesNotInput.Remove(id.Key);
}
//TODO: Gotta be a better way than a tryCount...
int tryCount = 0;
int nodeFromId = -1;
int nodeToId = -1;
while (tryCount < 20)
{
nodeFromId = allNodes.Keys.ToList()[rando.Next(allNodes.Count)];
nodeToId = allNodesNotInput.Keys.ToList()[rando.Next(allNodesNotInput.Count)];
if (!genome.ContainsConnection(nodeFromId, nodeToId))
{
break;
}
tryCount++;
}
if (tryCount == 20)
{
return;
}
ConnectionInformation connectInfo = new ConnectionInformation(nodeFromId, nodeToId);
InnovationInformation innovation = new InnovationInformation(connectInfo);
int connectId = -1;
//TODO: Pull inital weight setting out of here.
double weight = rando.NextDouble() * 2.0 - 1.0;
int registeredInnovationId = innovationsSeen.FindByInnovation(innovation);
if (registeredInnovationId == -1)
{
connectId = ConnectionPool.Add(connectInfo);
innovation.NewConnectionDetails.ConnectionId = connectId;
innovationsSeen.Add(innovation);
}
else
{
connectId = innovationsSeen.FindById(registeredInnovationId).NewConnectionDetails.ConnectionId;
}
genome.Genes.Add(new Gene(ConnectionPool.FindById(connectId), connectId, weight, false));
}
/// <summary>
/// Adds a new innovation to the pool.
/// </summary>
/// <param name="innovInfo">The information uniquely identifying the innovation.</param>
/// <returns>The position in the Pool (unique Id).</returns>
public int Add(InnovationInformation innovInfo)
{
Pool.Add(innovInfo);
return(Size() - 1);
}
