private Evolver()
{
var parameters = new RandomParameters(
new EdgeParameters(new Parameter(-1, 1, .005)),
new NodeParameters(
new Parameter(-1, 1, .005),
new FunctionParameters(.005, new Parameter(-1, 1, .005))
)
);
Func <Network, double> fitnessFunction = network => {
return(-Enumerable.Range(-5, 11).Select(i => (Math.Abs(network.Evaluate(new double[] { i })[0] - Math.Abs(i))))
.Sum());
};
var random = new Random();
var evolution = new Evolution(random, parameters, fitnessFunction)
{
Size = Size = new Size(700, 600),
Anchor = AnchorStyles.Top | AnchorStyles.Right | AnchorStyles.Bottom | AnchorStyles.Left
};
Controls.Add(evolution);
var layerSizes = new int[] { 1, 1, 1 };
evolution.SetNetworks(Enumerable.Range(0, 16).Select(i => CreateLayered(random, parameters, layerSizes))
.ToList());
evolution.Start();
}
public Evolution(Random randomGenerator, RandomParameters parameters, Func <Network, double> fitnessFunction)
{
SetStyle(ControlStyles.DoubleBuffer, true);
_randomGenerator = randomGenerator;
_parameters = parameters;
_fitnessFunction = fitnessFunction;
Controls.Add(interfaceContainer = new FlowLayoutPanel()
{
Anchor = AnchorStyles.Bottom | AnchorStyles.Top | AnchorStyles.Left | AnchorStyles.Right
});
interfaceContainer.FlowDirection = FlowDirection.TopDown;
interfaceContainer.Controls.Add(_iterationLabel = new Label());
interfaceContainer.Controls.Add(_fitnessLabel = new Label());
interfaceContainer.Controls.Add(_outputLabel = new Label()
{
AutoSize = true,
Font = new Font(FontFamily.GenericMonospace, 8)
});
interfaceContainer.Controls.Add(_networkLabel = new Label()
{
AutoSize = true,
Font = new Font(FontFamily.GenericMonospace, 8)
});
}
private static Network CreateLayered(Random random, RandomParameters randomParameters, IList <int> layerSizes)
{
var result = new Network();
var layers = layerSizes.Count;
var innovationNumber = 0;
var layerNodes = Enumerable.Range(0, layers)
.Select(i => Enumerable.Range(0, layerSizes[i])
.Select(a =>
result.AddNode(new Node(innovationNumber++, randomParameters.Node.Bias.GetNew(random))))
.ToArray())
.ToArray();
layerNodes[layers - 1].ToList()
.ForEach(node => node.ActivationFunction = new ActivationFunctions.LeakyRelu(1, 1));
result.InNodes = layerNodes[0];
result.OutNodes = layerNodes[layers - 1];
Enumerable.Range(0, layers - 1).ToList()
.ForEach(i => layerNodes[i + 1].ToList()
.ForEach(outNode => layerNodes[i].ToList()
.ForEach(inNode => result.AddEdge(
new Edge(innovationNumber++, randomParameters.Edge.Weight.GetNew(random), inNode, outNode)
))));
return(result);
}
public void Mutate(Random random, Func <long> innovationNumberGenerator, RandomParameters parameters)
{
_nodes.Values.ToList().ForEach(node => {
node.Mutate(random, parameters.Node);
if (random.NextDouble() < parameters.Node.RemoveRate)
{
_nodes.Remove(node.InnovationNumber);
return;
}
// TODO: Add S new edges (in which S follows a binomial distribution with parameters n = _nodes.Count * _nodes.Count and p = parameters.Edge.AddRate;
});
_edges.Values.ToList().ForEach(edge => {
edge.Mutate(random, parameters.Edge);
if (random.NextDouble() < parameters.Edge.RemoveRate ||
!_nodes.ContainsKey(edge.InNode.InnovationNumber) ||
!_nodes.ContainsKey(edge.OutNode.InnovationNumber))
{
_edges.Remove(edge.InnovationNumber);
return;
}
if (random.NextDouble() < parameters.Node.AddRate)
{
Func <Random, double> newWeight = parameters.Edge.Weight.GetNew;
Func <Random, double> newBias = parameters.Node.Bias.GetNew;
edge.OutNode.IncomingEdges.Remove(edge);
_edges.Remove(edge.InnovationNumber);
var newNode = AddNode(new Node(innovationNumberGenerator(), newBias(random)));
AddEdge(new Edge(innovationNumberGenerator(), newWeight(random), edge.InNode, newNode));
AddEdge(new Edge(innovationNumberGenerator(), newWeight(random), newNode, edge.OutNode));
}
});
}