public void Save(IntWeightDictionary weights, IntNeuronDictionary neurons)
{
this.weights = weights;
this.neurons = neurons;
BinaryFormatter bf = new BinaryFormatter();
FileStream file = File.Create(dataPath);
GameData data = new GameData();
data.weights = weights;
data.neurons = neurons;
bf.Serialize(file, data);
file.Close();
Debug.Log("Network saved!");
}
public void Draw(IntNeuronDictionary neurons, IntWeightDictionary weights)
{
if (neuronObjects != null)
{
foreach (var neuron in neuronObjects)
{
Destroy(neuron);
}
}
if (weightObjects != null)
{
foreach (var weight in weightObjects)
{
Destroy(weight);
}
}
neuronObjects = new List <GameObject>();
foreach (var neuron in neurons.Values)
{
neuronPositions[neuron.ID] = (neuron.splitX * maxX - 0.5f * maxX) * 2f;//Random.Range(-.35f, 1.4f) * maxX - 0.5f * maxX;
var neuronObject = Instantiate(neuronPrefab, transform.localPosition + new Vector3(neuronPositions[neuron.ID], neuron.splitY * maxY - 0.5f * maxY),
Quaternion.identity, transform).gameObject;
neuronObject.name = "Neuron" + neuron.ID;
neuronObjects.Add(neuronObject);
}
foreach (var weight in weights.Values)
{
var connection = Instantiate(weightPrefab, Vector3.zero, Quaternion.identity, transform);
renderer = connection.GetComponent <LineRenderer>();
renderer.startWidth = renderer.endWidth = lineWidth * weight.value;
var color = weight.value < 0f ? Color.red : Color.green;
color = weight.enabled ? color : Color.black;
renderer.startColor = renderer.endColor = color;
weightObjects.Add(connection);
var splitXNeuronIn = neuronPositions[weight.neuronIn]; //Random.Range(0f, 1f) * maxX - 0.5f * maxX;//neurons[weight.neuronIn].splitX * maxX - 0.5f * maxX;
var splitYNeuronIn = neurons[weight.neuronIn].splitY * maxY - 0.5f * maxY;
var splitXNeuronOut = neuronPositions[weight.neuronOut]; //Random.Range(0f, 1f) * maxX;// - 0.5f * maxX;//neurons[weight.neuronOut].splitX * maxX - 0.5f * maxX;
var splitYNeuronOut = neurons[weight.neuronOut].splitY * maxY - 0.5f * maxY;
DrawLine(new Vector3(splitXNeuronIn, splitYNeuronIn) + transform.localPosition, new Vector3(splitXNeuronOut, splitYNeuronOut) + transform.localPosition);
}
}
public bool Load()
{
if (File.Exists(dataPath))
{
BinaryFormatter bf = new BinaryFormatter();
FileStream file = File.Open(dataPath, FileMode.Open);
if (file.Length > 0)
{
GameData data = (GameData)bf.Deserialize(file);
file.Close();
weights = data.weights;
neurons = data.neurons;
}
return(true);
}
return(false);
}
public void MutateEnableDisable(bool enable)
{
var candidates = new IntWeightDictionary();
for (int i = 0; i < weights.Count; i++)
{
var weight = weights.ElementAt(i).Value;
if (weight.enabled != enable)
{
candidates.Add(i, weight);
}
}
if (candidates.Count == 0)
{
return;
}
var chosen = candidates.ElementAt(Random.Range(0, candidates.Count)).Value;
chosen.enabled = enable;
}
public Genome(IntNeuronDictionary neurons, IntWeightDictionary weights)
{
innovationDB = InnovationDB.instance;
this.neurons = neurons;
this.weights = weights;
}
public Genome()
{
innovationDB = InnovationDB.instance;
weights = new IntWeightDictionary();
neurons = new IntNeuronDictionary();
}
public Genome Crossover(Genome other)
{
var parentA = this;
var parentB = other;
Genome best = new Genome();
if (parentA.fitness == parentB.fitness)
{
// if same fitness pick shortest genome
if (parentA.NumGenes() < parentB.NumGenes())
{
best = parentA;
}
else if (parentB.NumGenes() < parentA.NumGenes())
{
best = parentB;
}
else
{
int randomElement = Random.Range(0, 2);
best = randomElement == 0 ? parentA : parentB;
}
}
else if (parentA.fitness > parentB.fitness)
{
best = parentA;
}
else
{
best = parentB;
}
var childWeights = new IntWeightDictionary();
var childNeurons = new IntNeuronDictionary();
int parentAIndex = 0, parentBIndex = 0;
Weight parentAWeight = null, parentBWeight = null;
// while end of both genes is not reached
while (parentAIndex < parentA.weights.Count || parentBIndex < parentB.weights.Count)
{
if (parentAIndex < parentA.weights.Count)
{
parentAWeight = parentA.weights.ElementAt(parentAIndex).Value.Copy();
}
if (parentBIndex < parentB.weights.Count)
{
parentBWeight = parentB.weights.ElementAt(parentBIndex).Value.Copy();
}
Weight selectedWeight = null;
if (parentAIndex == parentA.weights.Count && parentBIndex != parentB.weights.Count)
{
// add excess genes
if (parentB == best)
{
selectedWeight = parentBWeight;
}
parentBIndex++;
}
else if (parentBIndex == parentB.weights.Count && parentAIndex != parentA.weights.Count)
{
// add excess genes
if (parentA == best)
{
selectedWeight = parentAWeight;
}
parentAIndex++;
}
else if (parentAWeight.innovID < parentBWeight.innovID)
{
// add parentA disjoint genes
if (parentA == best)
{
selectedWeight = parentAWeight;
}
parentAIndex++;
}
else if (parentBWeight.innovID < parentAWeight.innovID)
{
// add parentB disjoint genes
if (parentB == best)
{
selectedWeight = parentBWeight;
}
parentBIndex++;
}
else
{
int randomElement = Random.Range(0, 2);
selectedWeight = randomElement == 0 ? parentAWeight : parentBWeight;
if (!parentAWeight.enabled && !parentBWeight.enabled)
{
float random = Random.value;
if (random <= pWeightEnabled)
{
selectedWeight.enabled = true;
}
}
parentAIndex++;
parentBIndex++;
}
if (selectedWeight != null && !childWeights.ContainsKey(selectedWeight.innovID))
{
childWeights.Add(selectedWeight.innovID, selectedWeight);
}
if (selectedWeight != null)
{
if (!childNeurons.ContainsKey(selectedWeight.neuronIn))
{
Neuron neuron = null;
if (parentA.weights.Any(x => x.Value.neuronIn == selectedWeight.neuronIn))
{
neuron = parentA.neurons[selectedWeight.neuronIn].Copy();
}
else if (parentB.weights.Any(x => x.Value.neuronIn == selectedWeight.neuronIn))
{
neuron = parentB.neurons[selectedWeight.neuronIn].Copy();
}
if (neuron == null)
{
Debug.LogError("NEURON IS NULL!");
}
childNeurons.Add(neuron.ID, neuron);
}
if (!childNeurons.ContainsKey(selectedWeight.neuronOut))
{
Neuron neuron = null;
if (parentA.weights.Any(x => x.Value.neuronOut == selectedWeight.neuronOut))
{
neuron = parentA.neurons[selectedWeight.neuronOut].Copy();
}
else if (parentB.weights.Any(x => x.Value.neuronOut == selectedWeight.neuronOut))
{
neuron = parentB.neurons[selectedWeight.neuronOut].Copy();
}
if (neuron == null)
{
Debug.LogError("NEURON IS NULL!");
}
childNeurons.Add(neuron.ID, neuron);
}
}
}
return(new Genome(childNeurons, childWeights));
}
