/// Finds a link and expands it
void AddNewHiddenNeuron()
{
if (linkCount == 0)
{
Debug.LogError("Cannot create new hidden neuron because link list count is zero");
return;
}
int randLinkID = Random.Range(0, linkCount);
// Create new neuron
//NeuronGenome newNeuronGenome = new NeuronGenome("HidNew", NeuronType.Hid, BrainModuleID.Undefined, hiddenNeurons.Count);
var newHiddenNeuron = new NeuronGenome(hiddenTemplate, inOutNeurons.Count + hiddenNeurons.Count);
hiddenNeurons.Add(newHiddenNeuron);
// create 2 new links
LinkGenome linkGenome1 = new LinkGenome(links[randLinkID].from, newHiddenNeuron, 1f, true);
LinkGenome linkGenome2 = new LinkGenome(newHiddenNeuron, links[randLinkID].to, links[randLinkID].weight, true);
// delete old link
links[randLinkID].enabled = false; // *** not needed? ****
links.RemoveAt(randLinkID);
// add new links
links.Add(linkGenome1);
links.Add(linkGenome2);
//Debug.Log("New Neuron! " + newNeuronGenome.nid.neuronID.ToString() +
// " - from: [" + linkGenome1.fromModuleID.ToString() + ", " +
// linkGenome1.fromNeuronID.ToString() + "], to: [" + linkGenome2.toModuleID.ToString() +
// ", " + linkGenome2.toNeuronID.ToString() + "]");
}
List <LinkGenome> MutateLinks(List <LinkGenome> original, MutationSettingsInstance settings)
{
var result = new List <LinkGenome>();
foreach (var element in original)
{
LinkGenome newLinkGenome = new LinkGenome(element.from, element.to, element.weight, true);
// Remove fully??? *****
if (RandomStatics.CoinToss(settings.brainRemoveLinkChance))
{
newLinkGenome.weight = 0f;
}
if (RandomStatics.CoinToss(settings.brainWeightMutationChance))
{
float randomWeight = Gaussian.GetRandomGaussian();
newLinkGenome.weight += Mathf.Lerp(0f, randomWeight, settings.brainWeightMutationStepSize);
}
newLinkGenome.weight *= settings.brainWeightDecayAmount;
result.Add(newLinkGenome);
}
return(result);
}
/// Apply a random chance of connecting two neurons with a random weight
void RequestConnection(NeuronGenome from, NeuronGenome to, float connectionChance, float weightMultiplier)
{
var connectNeurons = RandomStatics.CoinToss(connectionChance);
if (!connectNeurons)
{
return;
}
var randomWeight = Gaussian.GetRandomGaussian() * weightMultiplier;
var linkGenome = new LinkGenome(from, to, randomWeight, true);
links.Add(linkGenome);
}
void AddNewLink(MutationSettingsInstance settings)
{
foreach (var neuron in hiddenNeurons)
{
inputNeurons.Add(neuron);
outputNeurons.Add(neuron);
}
if (inputNeurons.Count <= 0 || outputNeurons.Count <= 0)
{
Debug.LogError("Cannot create new list because input or output list count is zero. " +
$"Input count = {inputNeurons.Count}, output count = {outputNeurons.Count}");
return;
}
// Try x times to find new connection -- random scattershot approach at first:
// other methods:
// -- make sure all bodyNeurons are fully-connected when modifying body
int maxChecks = 8;
for (int k = 0; k < maxChecks; k++)
{
int randInputID = Random.Range(0, inputNeurons.Count);
var from = inputNeurons[randInputID];
int randOutputID = Random.Range(0, outputNeurons.Count);
var to = outputNeurons[randOutputID];
if (LinkExists(from, to))
{
continue;
}
float randomWeight = Gaussian.GetRandomGaussian() * settings.brainWeightMutationStepSize;
LinkGenome linkGenome = new LinkGenome(from, to, randomWeight, true);
links.Add(linkGenome);
//Debug.Log("New Link! from: [" + fromNID.moduleID.ToString() + ", " + fromNID.neuronID.ToString() + "], to: [" + toNID.moduleID.ToString() + ", " + toNID.neuronID.ToString() + "]");
break;
}
}
public void CreateSpeciesLeaderboardGenomeTexture()
{
int width = 32;
int height = 96;
speciesPoolGenomeTex.Resize(width, height);
SpeciesGenomePool pool = simulationManager.GetSelectedGenomePool();
for (int x = 0; x < width; x++)
{
for (int y = 0; y < height; y++)
{
LinkGenome linkGenome = pool.GetLeaderboardLinkGenome(x, y);
Color testColor = linkGenome == null ? CLEAR : Color.Lerp(negativeColor, positiveColor, linkGenome.normalizedWeight);
speciesPoolGenomeTex.SetPixel(x, y, testColor);
}
}
// Body Genome
//int xI = curLinearIndex % speciesPoolGenomeTex.width;
//int yI = Mathf.FloorToInt(curLinearIndex / speciesPoolGenomeTex.width);
speciesPoolGenomeTex.Apply();
}
public void SetToMutatedCopyOfParentGenome(BrainGenome parentGenome, TrainingSettingsManager settings)
{
this.bodyNeuronList = parentGenome.bodyNeuronList; // UNSUSTAINABLE!!! might work now since all neuronLists are identical
// Alternate: SetBodyNeuronsFromTemplate(BodyGenome templateBody);
// Existing Hidden Neurons!!
hiddenNeuronList = new List <NeuronGenome>();
for (int i = 0; i < parentGenome.hiddenNeuronList.Count; i++)
{
NeuronGenome newHiddenNeuronGenome = new NeuronGenome(parentGenome.hiddenNeuronList[i]); // create new neuron as a copy of parent neuron
// Might be able to simply copy hiddenNeuronList or individual hiddenNeuronGenomes from parent if they are functionally identical...
// for now going with the thorough approach of a reference-less copy
hiddenNeuronList.Add(newHiddenNeuronGenome);
}
// Existing Links!!
linkList = new List <LinkGenome>();
for (int i = 0; i < parentGenome.linkList.Count; i++)
{
LinkGenome newLinkGenome = new LinkGenome(parentGenome.linkList[i].fromModuleID, parentGenome.linkList[i].fromNeuronID, parentGenome.linkList[i].toModuleID, parentGenome.linkList[i].toNeuronID, parentGenome.linkList[i].weight, true);
float randChance = UnityEngine.Random.Range(0f, 1f);
if (randChance < settings.mutationChance)
{
float randomWeight = Gaussian.GetRandomGaussian();
newLinkGenome.weight = Mathf.Lerp(newLinkGenome.weight, randomWeight, settings.mutationStepSize);
}
linkList.Add(newLinkGenome);
}
// Add Brand New Link:
//
float randLink = UnityEngine.Random.Range(0f, 1f);
if (randLink < settings.newLinkChance)
{
List <NeuronGenome> inputNeuronList = new List <NeuronGenome>();
//List<NeuronGenome> hiddenNeuronList = new List<NeuronGenome>();
List <NeuronGenome> outputNeuronList = new List <NeuronGenome>();
for (int j = 0; j < bodyNeuronList.Count; j++)
{
if (bodyNeuronList[j].neuronType == NeuronGenome.NeuronType.In)
{
inputNeuronList.Add(bodyNeuronList[j]);
}
if (bodyNeuronList[j].neuronType == NeuronGenome.NeuronType.Out)
{
outputNeuronList.Add(bodyNeuronList[j]);
}
}
for (int j = 0; j < hiddenNeuronList.Count; j++)
{
inputNeuronList.Add(hiddenNeuronList[j]);
outputNeuronList.Add(hiddenNeuronList[j]);
}
// Try x times to find new connection -- random scattershot approach at first:
// other methods:
// -- make sure all bodyNeurons are fully-connected when modifying body
int maxChecks = 8;
for (int k = 0; k < maxChecks; k++)
{
int randID = UnityEngine.Random.Range(0, inputNeuronList.Count);
NID fromNID = inputNeuronList[randID].nid;
randID = UnityEngine.Random.Range(0, outputNeuronList.Count);
NID toNID = outputNeuronList[randID].nid;
// check if it exists:
bool linkExists = false;
for (int l = 0; l < linkList.Count; l++)
{
if (linkList[l].fromModuleID == fromNID.moduleID && linkList[l].fromNeuronID == fromNID.neuronID && linkList[l].toModuleID == toNID.moduleID && linkList[l].toNeuronID == toNID.neuronID)
{
linkExists = true;
break;
}
}
if (linkExists)
{
}
else
{
float randomWeight = Gaussian.GetRandomGaussian() * 0f;
LinkGenome linkGenome = new LinkGenome(fromNID.moduleID, fromNID.neuronID, toNID.moduleID, toNID.neuronID, randomWeight, true);
//Debug.Log("New Link! from: [" + fromNID.moduleID.ToString() + ", " + fromNID.neuronID.ToString() + "], to: [" + toNID.moduleID.ToString() + ", " + toNID.neuronID.ToString() + "]");
linkList.Add(linkGenome);
break;
}
}
}
// Add Brand New Hidden Neuron:
float randNeuronChance = UnityEngine.Random.Range(0f, 1f);
if (randNeuronChance < settings.newHiddenNodeChance)
{
// find a link and expand it:
int randLinkID = UnityEngine.Random.Range(0, linkList.Count);
// create new neuron
NeuronGenome newNeuronGenome = new NeuronGenome(NeuronGenome.NeuronType.Hid, -1, hiddenNeuronList.Count);
hiddenNeuronList.Add(newNeuronGenome);
// create 2 new links
LinkGenome linkGenome1 = new LinkGenome(linkList[randLinkID].fromModuleID, linkList[randLinkID].fromNeuronID, newNeuronGenome.nid.moduleID, newNeuronGenome.nid.neuronID, 1f, true);
LinkGenome linkGenome2 = new LinkGenome(newNeuronGenome.nid.moduleID, newNeuronGenome.nid.neuronID, linkList[randLinkID].toModuleID, linkList[randLinkID].toNeuronID, linkList[randLinkID].weight, true);
// delete old link
linkList.RemoveAt(randLinkID);
// add new links
linkList.Add(linkGenome1);
linkList.Add(linkGenome2);
//Debug.Log("New Neuron! " + newNeuronGenome.nid.neuronID.ToString() + " - from: [" + linkGenome1.fromModuleID.ToString() + ", " + linkGenome1.fromNeuronID.ToString() + "], to: [" + linkGenome2.toModuleID.ToString() + ", " + linkGenome2.toNeuronID.ToString() + "]");
}
}
public void InitializeAxons(float initialWeightMultiplier)
{
int numInputs = 0;
for (int i = 0; i < bodyNeuronList.Count; i++)
{
if (bodyNeuronList[i].neuronType == NeuronGenome.NeuronType.In)
{
numInputs++;
}
}
// !!!!! ===== UPGRADE NOTE: !!!!!!!!!!!!
// Add support for initial traditional hidden layers - generalize down to 0 to support all initializations
// !!!!! ===== UPGRADE NOTE: !!!!!!!!!!!!
// Create Hidden nodes TEMP!!!!
for (int i = 0; i < numInputs; i++)
{
//NeuronGenome neuron = new NeuronGenome(NeuronGenome.NeuronType.Hid, 20, i);
//brainGenome.neuronList.Add(neuron);
}
// Create initial connections -- :
List <NeuronGenome> inputNeuronList = new List <NeuronGenome>();
//List<NeuronGenome> hiddenNeuronList = new List<NeuronGenome>();
List <NeuronGenome> outputNeuronList = new List <NeuronGenome>();
for (int i = 0; i < bodyNeuronList.Count; i++)
{
if (bodyNeuronList[i].neuronType == NeuronGenome.NeuronType.In)
{
inputNeuronList.Add(bodyNeuronList[i]);
}
//if (brainGenome.neuronList[i].neuronType == NeuronGenome.NeuronType.Hid) {
// hiddenNeuronList.Add(brainGenome.neuronList[i]);
//}
if (bodyNeuronList[i].neuronType == NeuronGenome.NeuronType.Out)
{
outputNeuronList.Add(bodyNeuronList[i]);
}
}
// Initialize fully connected with all weights Random
for (int i = 0; i < outputNeuronList.Count; i++)
{
for (int j = 0; j < inputNeuronList.Count; j++)
{
float randomWeight = Gaussian.GetRandomGaussian() * initialWeightMultiplier;
LinkGenome linkGenome = new LinkGenome(inputNeuronList[j].nid.moduleID, inputNeuronList[j].nid.neuronID, outputNeuronList[i].nid.moduleID, outputNeuronList[i].nid.neuronID, randomWeight, true);
linkList.Add(linkGenome);
}
}
/*for (int i = 0; i < outputNeuronList.Count; i++) {
* for(int j = 0; j < hiddenNeuronList.Count; j++) {
* float randomWeight = Gaussian.GetRandomGaussian() * initialWeightMultiplier;
* LinkGenome linkGenome = new LinkGenome(hiddenNeuronList[j].nid.moduleID, hiddenNeuronList[j].nid.neuronID, outputNeuronList[i].nid.moduleID, outputNeuronList[i].nid.neuronID, randomWeight, true);
* brainGenome.linkList.Add(linkGenome);
* }
* }
* for (int i = 0; i < hiddenNeuronList.Count; i++) {
* for (int j = 0; j < inputNeuronList.Count; j++) {
* float randomWeight = Gaussian.GetRandomGaussian() * initialWeightMultiplier;
* LinkGenome linkGenome = new LinkGenome(inputNeuronList[j].nid.moduleID, inputNeuronList[j].nid.neuronID, hiddenNeuronList[i].nid.moduleID, hiddenNeuronList[i].nid.neuronID, randomWeight, true);
* brainGenome.linkList.Add(linkGenome);
* }
* }*/
//PrintBrainGenome();
}
public void InitializeAxons(float initialWeightMultiplier)
{
int numInputs = 0;
for (int i = 0; i < bodyNeuronList.Count; i++)
{
if (bodyNeuronList[i].neuronType == NeuronGenome.NeuronType.In)
{
numInputs++;
}
}
// Create Hidden nodes TEMP!!!!
for (int i = 0; i < numInputs; i++)
{
NeuronGenome neuron = new NeuronGenome(NeuronGenome.NeuronType.Hid, -1, i);
hiddenNeuronList.Add(neuron);
}
// Create initial connections -- :
List <NeuronGenome> inputNeuronList = new List <NeuronGenome>();
//List<NeuronGenome> hiddenNeuronList = new List<NeuronGenome>();
List <NeuronGenome> outputNeuronList = new List <NeuronGenome>();
for (int i = 0; i < bodyNeuronList.Count; i++)
{
if (bodyNeuronList[i].neuronType == NeuronGenome.NeuronType.In)
{
inputNeuronList.Add(bodyNeuronList[i]);
}
//if (brainGenome.neuronList[i].neuronType == NeuronGenome.NeuronType.Hid) {
// hiddenNeuronList.Add(brainGenome.neuronList[i]);
//}
if (bodyNeuronList[i].neuronType == NeuronGenome.NeuronType.Out)
{
outputNeuronList.Add(bodyNeuronList[i]);
}
}
// Initialize fully connected with all weights Random
for (int i = 0; i < outputNeuronList.Count; i++)
{
for (int j = 0; j < inputNeuronList.Count; j++)
{
float randomWeight = Gaussian.GetRandomGaussian() * initialWeightMultiplier;
LinkGenome linkGenome = new LinkGenome(inputNeuronList[j].nid.moduleID, inputNeuronList[j].nid.neuronID, outputNeuronList[i].nid.moduleID, outputNeuronList[i].nid.neuronID, randomWeight, true);
linkList.Add(linkGenome);
}
}
for (int i = 0; i < outputNeuronList.Count; i++)
{
for (int j = 0; j < hiddenNeuronList.Count; j++)
{
float randomWeight = Gaussian.GetRandomGaussian() * initialWeightMultiplier;
LinkGenome linkGenome = new LinkGenome(hiddenNeuronList[j].nid.moduleID, hiddenNeuronList[j].nid.neuronID, outputNeuronList[i].nid.moduleID, outputNeuronList[i].nid.neuronID, randomWeight, true);
linkList.Add(linkGenome);
}
}
for (int i = 0; i < hiddenNeuronList.Count; i++)
{
for (int j = 0; j < inputNeuronList.Count; j++)
{
float randomWeight = Gaussian.GetRandomGaussian() * initialWeightMultiplier;
LinkGenome linkGenome = new LinkGenome(inputNeuronList[j].nid.moduleID, inputNeuronList[j].nid.neuronID, hiddenNeuronList[i].nid.moduleID, hiddenNeuronList[i].nid.neuronID, randomWeight, true);
linkList.Add(linkGenome);
}
}
//PrintBrainGenome();
//Debug.Log("numAxons: " + linkList.Count.ToString());
}
