public override void MutateWeightShift(ChaoticSeer seer)
{
ConnectionGene con = seer.Connections.Random;
if (con != null)
{
con.Weight += ((Rng.GetRngF() * 2) - 1) * NeatCNS.WEIGHT_SHIFT_STRENGTH;
}
}
static void Main(string[] args)
{
NeatCNS neat = new NeatCNS(3, 3, 100);
ChaoticSeer g = new ChaoticSeer(neat);
//Genome g = neat.NewEmptyGenome();
Console.WriteLine(g.Nodes.Count);
Console.ReadKey();
}
public override void MutateToggleConnection(ChaoticSeer seer)
{
ConnectionGene con = seer.Connections.Random;
if (con != null)
{
con.IsEnabled = con.IsEnabled;
}
}
private void GeneticsTest_Load(object sender, EventArgs e)
{
tribe = new TribeST(2, 1, 10);
region = new RegionST(3, 2, 1, 10);
genomeRepresentative = tribe.Species[0];
pictureBoxes = new PictureBox[tribe.Species.Count];
InitializePictureBoxes();
Console.WriteLine("Nodes: " + genomeRepresentative.Nodes.Count);
Console.WriteLine("Connections: " + genomeRepresentative.Connections.Count);
}
public override void MutateNode(ChaoticSeer seer)
{
if (seer.Nodes.Count >= NeatCNS.MAX_NODES)
{
return; // Cap nodes
}
if (seer.Nodes.Count >= NeatCNS.T_MAX_NODES)
{
return; // Cap nodes
}
ConnectionGene con = seer.Connections.Random;
if (con == null)
{
return;
}
NodeGene from = con.From;
NodeGene middle;
NodeGene to = con.To;
int replaceIndex = Sg.Neat.GetReplaceIndex(from, to);
if (replaceIndex == 0)
{
middle = Sg.Neat.AddNode();
middle.X = (from.X + to.X) / 2;
middle.Y = (from.Y + to.Y) / 2 + (float)((Rng.GetRngF() * 0.1) - 0.05);
Sg.Neat.SetReplaceIndex(from, to, middle.InnovationNumber);
}
else
{
middle = Sg.Neat.AddNode(replaceIndex);
}
//NodeGene middle = Neat.AddNode();
//middle.X = (from.X + to.X) / 2; //Divide by to to get the center
//middle.Y = (from.Y + to.Y) / 2; //Divide by to to get the center
ConnectionGene con1 = Sg.Neat.AddConnection(from, middle);
ConnectionGene con2 = Sg.Neat.AddConnection(middle, to);
con1.Weight = 1;
con2.Weight = con.Weight;
con2.IsEnabled = con.IsEnabled;
seer.Connections.Remove(con);
seer.Connections.Add(con1);
seer.Connections.Add(con2);
seer.Nodes.Add(middle);
}
public override void MutateConnection(ChaoticSeer seer)
{
for (int i = 0; i < 100; i++)
{
NodeGene a = seer.Nodes.Random;
NodeGene b = seer.Nodes.Random;
if (a == null || b == null)
{
continue; //skip if empty
}
if (a.X == b.X)
{
continue; //skip if thesame
}
// Create connection for the new seed
ConnectionGene con;
if (a.X < b.X)
{
con = new ConnectionGene(a, b);
}
else
{
con = new ConnectionGene(b, a);
}
if (seer.Connections.Contains(con))
{
//skip if newly generated connection already exist
continue;
}
con = Sg.Neat.AddConnection(con.From, con.To);
con.Weight = ((Rng.GetRngF() * 2) - 1) * NeatCNS.WEIGHT_RANDOM_STRENGTH;
//Attempt to ensure that the data is sorted by its InnovaitonNumber
for (int cI = 0; i < seer.Connections.Count; i++)
{
int innovation = seer.Connections[cI].InnovationNumber;
if (con.InnovationNumber < innovation)
{
//Insert it right next
seer.Connections.Insert(cI, con);
return;
}
}
seer.Connections.Add(con);
return;
}
}
public FPropagateST(ChaoticSeer seer)
{
InputNodes = new List <CalcNode>();
HiddenNodes = new List <CalcNode>();
OutputNodes = new List <CalcNode>();
GeneHashSet <NodeGene> _nodes = seer.Nodes;
GeneHashSet <ConnectionGene> _cons = seer.Connections;
Dictionary <int, CalcNode> _nodeHashMap = new Dictionary <int, CalcNode>();
foreach (NodeGene item in _nodes.Data)
{
CalcNode node = new CalcNode(item.X);
_nodeHashMap.Add(item.InnovationNumber, node);
if (item.X <= 0.1f)
{
InputNodes.Add(node);
}
else if (item.X >= 0.9f)
{
OutputNodes.Add(node);
}
else
{
HiddenNodes.Add(node);
}
}
HiddenNodes.Sort(); //This thing is working correct
foreach (ConnectionGene item in _cons.Data)
{
NodeGene from = item.From;
NodeGene to = item.To;
CalcNode node_from = _nodeHashMap[from.InnovationNumber];
CalcNode node_to = _nodeHashMap[to.InnovationNumber];
CalcConnection con = new CalcConnection(node_from, node_to)
{
Weight = item.Weight,
IsEnabled = item.IsEnabled
};
node_to.Connections.Add(con);
}
}
public override void Reproduce()
{
//Currently it will just fill up to max population
// TODO: add something to prevent mating with self
//for (int i = 0; i < 1; i++) {
// ChaoticSeer _seerX = Species.Random;
// ChaoticSeer _seerY = Species[i];
// ChaoticSeer _seerChild = _seerY.MateWith(_seerX);
// _seerChild.Identity = _seerX.Identity + _seerY.Identity;
// Species.Add(_seerChild);
//}
do
{
ChaoticSeer _seerX = Species.Random;
ChaoticSeer _seerY = Species.Random;
ChaoticSeer _seerChild = _seerX.MateWith(_seerY);
_seerChild.Identity = _seerX.Identity + _seerY.Identity;
Species.Add(_seerChild);
} while (Species.Count < MAX_POPULATION);
}
/// <summary> /// Creates a new genome based on two genomes /// </summary> /// <param name="g1">X Genome</param> /// <param name="g2">Y Genome</param> /// <returns></returns> public abstract ChaoticSeer CrossOver(ChaoticSeer g1, ChaoticSeer g2);
/// <summary> /// Toggle connection /// </summary> public abstract void MutateToggleConnection(ChaoticSeer seer);
/// <summary> /// Shift weight based on random strength /// </summary> public abstract void MutateWeightRandom(ChaoticSeer seer);
/// <summary> /// Shift weight based on shift strength /// </summary> public abstract void MutateWeightShift(ChaoticSeer seer);
/// <summary> /// Add node /// </summary> public abstract void MutateNode(ChaoticSeer seer);
public static Bitmap GenBitmap(ChaoticSeer _seer)
{
Bitmap Bm;
int PictureScale = 1;
//PictureScale = 1;
Pen connectionPen = new Pen(Color.Blue);
SolidBrush nodeBrush = new SolidBrush(Color.Green);
SolidBrush textBrushWhite = new SolidBrush(Color.White);
SolidBrush textBrushBlack = new SolidBrush(Color.Black);
Point[] nodePoints = NodeToPoints(_seer.Nodes.ToArray());
Point[][] connectionPoints = ConnectionsToPoint(_seer.Connections.ToArray());
float CanvasWidth = 100; //Limit the minimun size
float CanvasHeight = 100; //Limit the minimun size
//Get the largest point
for (int i = 0; i < nodePoints.Length; i++)
{
CanvasWidth = Math.Max(nodePoints[i].X, CanvasWidth);
CanvasHeight = Math.Max(nodePoints[i].Y, CanvasHeight);
}
CanvasWidth += 10;
CanvasHeight += 10;
Bm = new Bitmap(
(int)(PictureScale * CanvasWidth),
(int)(PictureScale * CanvasHeight));
//Console.WriteLine("Canvas Size: " + CanvasWidth + " x " + CanvasHeight);
//Console.WriteLine("Nodes: " + _seer.Nodes.Count);
//Console.WriteLine("Connections: " + _seer.Connections.Count);
Graphics gr = Graphics.FromImage(Bm);
gr.Clear(Color.AliceBlue);
gr.SmoothingMode = System.Drawing.Drawing2D.SmoothingMode.AntiAlias;
gr.ScaleTransform(PictureScale, PictureScale);
Rectangle[] rectangles = new Rectangle[nodePoints.Length];
////Draw line
//gr.DrawCurve(connectionPen, nodePoints, 0.0f);
for (int i = 0; i < connectionPoints.Length; i++)
{
gr.DrawLine(connectionPen, connectionPoints[i][0], connectionPoints[i][1]);
}
//Draw circle/node
for (int i = 0; i < nodePoints.Length; i++)
{
Point _offset = nodePoints[i];
_offset.Offset(-8, -8);
rectangles[i] = new Rectangle(_offset, new Size(16, 16));
}
foreach (Rectangle item in rectangles)
{
gr.FillEllipse(nodeBrush, item);
}
//Draw text InnovationNumber
//gr.DrawString("ASDF", new Font("Arial", 16), textBrush, new Point(10,10));
for (int i = 0; i < nodePoints.Length; i++)
{
Point _offset = nodePoints[i];
_offset.Offset(-5, -7);
gr.DrawString("" + _seer.Nodes[i].InnovationNumber, new Font("Courier New", 8), textBrushWhite, _offset);
//rectangles[i] = new Rectangle(_offset, new Size(10, 10));
}
//Draw text Status
string status = "Identity: " + _seer.Identity + Environment.NewLine +
"Fitness: " + _seer.Fitness + Environment.NewLine +
"Day: " + _seer.Day + Environment.NewLine +
"Age: " + _seer.Year;
gr.DrawString(status, new Font("Courier New", 8), textBrushBlack, new Point(600, 0));
//picCanvas.Image = Bm;
return(Bm);
}
public override ChaoticSeer CrossOver(ChaoticSeer g1, ChaoticSeer g2)
{
/// current g1 should have the higher score
/// take all the genes of g1
/// if there is a genome in g1 that is also in g2, choose randomly
/// do not take disjoint genes of g2
/// take excess genes of g1 if they exist
// NeatCNS neat = g1.Cns;
//Genome _genomeBuffer = neat.NewEmptyGenome();
ChaoticSeer _genomeBuffer = new ChaoticSeer();
int indexG1 = 0;
int indexG2 = 0;
//Handle not connectec genes
while (indexG1 < g1.Connections.Count && indexG2 < g2.Connections.Count)
{
ConnectionGene gene1 = g1.Connections[indexG1];
ConnectionGene gene2 = g2.Connections[indexG2];
//Because I seperated the client, the innovation number for them is different. This is a problem
int in1 = gene1.InnovationNumber;
int in2 = gene2.InnovationNumber;
if (in1 == in2)
{
// basically if they are thesame, just select either of them randomly
if (Rng.GetRngF() > 0.5f)
{
_genomeBuffer.Connections.Add(Sg.Neat.Connections[gene1]);
}
else
{
_genomeBuffer.Connections.Add(Sg.Neat.Connections[gene2]);
}
indexG1++;
indexG2++;
}
else if (in1 > in2)
{
//genome.Connections.Add(neat.Connections[gene2]);
//disjoint/skip gene of b
indexG2++;
}
else
{
//disjoint/skip gene of a
_genomeBuffer.Connections.Add(Sg.Neat.Connections[gene1]);
indexG1++;
}
}
// Add the connections
while (indexG1 < g1.Connections.Count)
{
ConnectionGene gene1 = g1.Connections[indexG1];
_genomeBuffer.Connections.Add(Sg.Neat.Connections[gene1]);
indexG1++;
}
// Add the nodes
foreach (ConnectionGene c in _genomeBuffer.Connections)
{
_genomeBuffer.Nodes.Add(c.From);
_genomeBuffer.Nodes.Add(c.To);
}
return(_genomeBuffer);
}