/// <summary>
/// Makes the initial connections frome every inout to every output with random weights.
/// </summary>
public void InitializeRandom()
{
for (int i = NumInputs; i < NumInputs + NumOutputs; i++)
{
Neurons.TryGetValue(i, out Neuron outputNeuron);
for (int j = 1; j < NumInputs; j++)
{
Neurons.TryGetValue(j, out Neuron inputNeuron);
Tuple <int, int> fromToPair = new Tuple <int, int>(inputNeuron.ID, outputNeuron.ID);
Connection conn;
if (InnovationNumbers.ContainsKey(fromToPair))
{
lock (InnovationNumbers)
{
InnovationNumbers.TryGetValue(fromToPair, out int innoNumber);
conn = new Connection(innoNumber, inputNeuron, rand.NextDouble() * 4 - 2);
}
}
else
{
lock (InnovationNumbers)
{
conn = new Connection(InnovationNumbers.Count(), inputNeuron, rand.NextDouble() * 4 - 2);
InnovationNumbers.Add(new Tuple <int, int>(inputNeuron.ID, outputNeuron.ID), InnovationNumbers.Count());
}
}
Connections.Add(fromToPair);
outputNeuron.AddConnection(conn.ID, conn);
}
}
}
/// <summary>
/// mutates a random link in the neural network
/// </summary>
public void MutateNeuron()
{
while (true)
{
int neuronId = rand.Next(NumInputs, NumInputs + NumOutputs);
if (Neurons.TryGetValue(neuronId, out Neuron farNeuron) && farNeuron.Connections.Count > 0)
{
Connection conn;
int connectionId;
do
{
connectionId = rand.Next(farNeuron.Connections.Count());
conn = farNeuron.Connections.Values.ElementAt(connectionId);
} while (conn.From.ID == 0);
Neuron newNeuron = new Neuron(Neurons.Count);
Tuple <int, int> nearToMidTuple = new Tuple <int, int>(conn.From.ID, newNeuron.ID);
Connection nearToMid;
lock (InnovationNumbers)
{
if (InnovationNumbers.TryGetValue(nearToMidTuple, out int innoNumber))
{
nearToMid = new Connection(innoNumber, conn.From, 1);
}
else
{
nearToMid = new Connection(InnovationNumbers.Count(), conn.From, 1);
InnovationNumbers.Add(nearToMidTuple, InnovationNumbers.Count());
}
}
Connection midToFar;
Tuple <int, int> midToFarTuple = new Tuple <int, int>(newNeuron.ID, farNeuron.ID);
lock (InnovationNumbers)
{
if (InnovationNumbers.TryGetValue(midToFarTuple, out int innoNumber2))
{
midToFar = new Connection(innoNumber2, newNeuron, conn.Weight);
}
else
{
midToFar = new Connection(InnovationNumbers.Count(), newNeuron, conn.Weight);
InnovationNumbers.Add(midToFarTuple, InnovationNumbers.Count());
}
}
Neurons.Add(newNeuron.ID, newNeuron);
newNeuron.AddConnection(nearToMid.ID, nearToMid);
Connection oldConnection = farNeuron.Connections.Values.ElementAt(connectionId);
conn.EnableDisable();
Connections.Add(nearToMidTuple);
Connections.Add(midToFarTuple);
farNeuron.AddConnection(midToFar.ID, midToFar);
NumNeurons++;
return;
}
}
}
/// <summary>
/// Mutates a random link whithin the neural network.
/// </summary>
public void MutateLink()
{
int from;
int to;
Stopwatch sw = new Stopwatch();
sw.Start();
do
{
rand = new Random(Guid.NewGuid().GetHashCode());
do
{
rand = new Random(Guid.NewGuid().GetHashCode());
from = rand.Next(Neurons.Count());
} while (from > NumInputs - 1 && from < NumInputs + NumOutputs);
do
{
rand = new Random(Guid.NewGuid().GetHashCode());
to = rand.Next(NumInputs, Neurons.Count());
} while (to == from || to < NumInputs || (to < from && to >= NumInputs + NumOutputs));
if (sw.ElapsedMilliseconds > 10)
{
return;
}
} while (Connections.Contains(new Tuple <int, int>(from, to)));
if (Neurons.TryGetValue(to, out Neuron toNeuron))
{
if (Neurons.TryGetValue(from, out Neuron fromNeuron))
{
Tuple <int, int> fromToPair = new Tuple <int, int>(from, to);
Connection conn;
if (InnovationNumbers.ContainsKey(fromToPair))
{
lock (InnovationNumbers)
{
InnovationNumbers.TryGetValue(fromToPair, out int innoNumber);
conn = new Connection(innoNumber, fromNeuron, rand.NextDouble() * 4 - 2);
}
}
else
{
lock (InnovationNumbers)
{
conn = new Connection(InnovationNumbers.Count(), fromNeuron, rand.NextDouble() * 4 - 2);
InnovationNumbers.Add(new Tuple <int, int>(from, to), InnovationNumbers.Count());
}
}
Connections.Add(fromToPair);
toNeuron.AddConnection(conn.ID, conn);
}
}
}
